#BigQuery FAQ | Explore Tumblr posts and blogs

eternalelevator · 2 hours ago

Text

Stop Guessing, Start Tracking: 10 Essential GA4 Events That Actually Drive Growth

If you’ve made the switch to Google Analytics 4 (GA4), congratulations—you’re now using one of the most powerful digital analytics tools available. But power means nothing if you're not tracking the right events.

GA4 is built for customization, and that flexibility is a blessing… and a curse. Too many marketers fall into two traps:

Tracking everything (and drowning in data)

Tracking nothing meaningful (and flying blind)

So what should you track in GA4? Let’s break down the 10 most essential events that every business—eCommerce, service-based, SaaS, or content-driven—should track to make smarter decisions and drive real results.

🔹 1. Page Views (Automatically Tracked)

Yes, GA4 tracks this by default. But don’t ignore it—page views help you spot top-performing content, funnel drop-offs, and page engagement trends.

✅ Use it to:

Analyze content popularity

Optimize site structure and UX

Spot bounce-prone pages

🔹 2. Scroll Depth

GA4 tracks a basic "scroll" event by default (90% scroll). But it’s smart to customize scroll tracking to measure engagement at 25%, 50%, 75%, and 100%.

✅ Use it to:

Identify where users drop off

Optimize long-form content

Improve call-to-action (CTA) placement

🔹 3. Outbound Link Clicks

This tells you when users click links leading off your site—to affiliates, partner sites, or social profiles.

✅ Use it to:

Measure affiliate performance

Monitor user journeys beyond your site

Optimize link placements

🔹 4. File Downloads

If you offer downloadable PDFs, guides, whitepapers, or lead magnets, this is a critical engagement signal.

✅ Use it to:

Track lead magnet success

Score and segment engaged users

Improve resource CTA copy and design

🔹 5. Video Engagement

GA4 tracks embedded YouTube video activity (play, progress, complete). If video is part of your strategy, don’t ignore this.

✅ Use it to:

Discover which videos hold attention

Optimize content length and hook

Increase conversion around high-engagement media

🔹 6. Site Search

Tracking what users search for within your website gives you direct insight into user intent and pain points.

✅ Use it to:

Identify missing or unclear content

Improve navigation and product discovery

Add FAQs based on top queries

🔹 7. Form Submissions

If your business relies on contact forms, lead forms, or sign-ups, you need to track every submission event.

✅ Use it to:

Measure lead quality and funnel effectiveness

Optimize forms for UX

Track conversion by traffic source

🔹 8. Add to Cart & Begin Checkout

For eCommerce brands, these are micro-conversions you absolutely need. They help you optimize before a full purchase even happens.

✅ Use it to:

Spot cart abandonment issues

Analyze product interest trends

A/B test product page layouts

🔹 9. Purchase (or Final Conversion)

This is your main KPI if you're in eCommerce or tracking paid signups. Make sure this is set up with transaction value and product details for ROAS analysis.

✅ Use it to:

Track true ROI

Attribute revenue to channels and campaigns

Measure lifetime value (LTV) with BigQuery

🔹 10. Custom Events (Based on Your Business Goals)

Think outside the box. Do you want to track newsletter sign-ups, pricing page views, or account upgrades? Custom events are where GA4 shines.

✅ Use it to:

Align analytics with your unique funnel

Score leads based on behavior

Prioritize top-performing UX flows

⚠️ Common Mistake to Avoid:

Don’t set up dozens of events just because you can. Every event should map to a business goal, a funnel stage, or a meaningful customer action.

✅ Final Thought: Track What Matters, Ignore the Noise

GA4 isn’t just a tracking tool—it’s your growth dashboard. But to get value from it, you must track events that tell a story: where users came from, what they did, and what moved them closer to conversion.

Focus less on vanity metrics and more on actionable data that helps you improve UX, boost conversions, and scale smarter.

#GA4Tips #GoogleAnalytics2025 #MarketingAnalytics #ConversionTracking #DataDrivenMarketing

0 notes

yfthg · 17 days ago

Text

Top Most Effective Customer Journey Analytics Solutions in Airlines

NUMR CXM: Elevating Airline Passenger Experience with Real-Time Journey Analytics

NUMR CXM is redefining customer journey analytics in the airline industry. By mapping end-to-end passenger interactions—from flight search to post-flight feedback—NUMR enables airlines to visualize customer drop-offs, delays in service, and satisfaction triggers. Using AI-powered predictive insights and omnichannel integration, NUMR CXM helps carriers proactively address pain points, increase loyalty, and maximize revenue per traveler. Airlines leveraging NUMR’s platform benefit from smarter segmentation, real-time action triggers, and optimized NPS across the journey lifecycle.

Why Customer Journey Analytics Matters in Aviation

In the hyper-competitive airline space, customer loyalty is fragile and influenced by multiple micro-moments—from ticket booking and check-in to baggage handling and flight experience. Customer journey analytics empowers airlines to:

Pinpoint moments of friction

Track engagement across mobile, web, and airport touchpoints

Deliver personalized interventions in real time

Improve operational efficiency and CX KPIs

Top Customer Journey Analytics Solutions in Airlines (2025)

1. NUMR CXM

AI-powered journey mapping tailored to aviation

Omnichannel passenger data integration

Predictive churn and loyalty insights

Personalized NPS and real-time feedback loops

2. Adobe Experience Platform

Real-time customer profile unification

Journey orchestration across devices

Visualization of path-to-purchase in airline portals

3. Salesforce Customer 360

Travel-specific CX dashboards

AI-driven service insights for call centers and loyalty programs

Integration with airline CRM and booking systems

4. Qualtrics Experience iD

Deep integration with operational data (e.g., delay reports)

Real-time surveys at critical travel moments

Voice-of-Customer (VoC) insights to prevent churn

5. Google Analytics 4 (GA4) with BigQuery

Tracks digital touchpoints pre-booking to boarding

Combines site behavior with predictive purchase modeling

Great for low-cost carriers optimizing conversion

6. Genesys Cloud CX

Advanced contact center analytics

Tracks call/chat/email journey interruptions

Identifies emotional sentiment in service breakdowns

7. Mixpanel

Granular event tracking on airline apps

Useful for enhancing loyalty program interaction

A/B testing and funnel analysis for digital CX teams

8. Medallia Experience Cloud

Real-time survey triggers based on NPS dips

Great airport and inflight service integration

Customizable reporting for route-level CX management

9. Sprinklr Unified CXM

Social media journey insights across platforms

Tracks complaints, praises, and competitor comparison

Excellent for airline brand reputation monitoring

10. SAS Customer Intelligence 360

Predictive personalization for frequent flyer programs

Advanced segmentation of leisure vs business travelers

Supports real-time marketing engagement

Geographic Insight: Journey Analytics in Indian and Global Aviation

India’s airline sector is experiencing explosive growth with increasing digital bookings and higher CX expectations. Globally, airlines in North America and the Middle East are leading in AI-driven journey analytics adoption. NUMR CXM is well-positioned to serve both these markets with scalable, agile platforms.

FAQs – Airline Journey Analytics Solutions

What is customer journey analytics in aviation?

It refers to the process of tracking and analyzing every interaction a passenger has with an airline, across all channels and touchpoints.

How does NUMR CXM enhance passenger experience?

NUMR CXM uses AI and predictive analytics to identify friction points in real time, enabling airlines to act quickly and improve satisfaction and loyalty.

Can airlines personalize experiences using journey data?

Yes, by mapping behavior and preferences, airlines can personalize offers, services, and communication at every journey stage.

Which journey stages are most prone to dissatisfaction?

Common friction points include booking, baggage claim, delay management, and customer service interactions.

Final Takeaway

Customer journey analytics is no longer optional—it's essential for airlines striving to deliver seamless, memorable travel experiences. By leveraging platforms like NUMR CXM, aviation brands can transform every touchpoint into an opportunity for delight, loyalty, and competitive differentiation in 2025 and beyond.

0 notes

govindhtech · 7 months ago

Text

Dataplex Automatic Discovery & Cataloging For Cloud Storage

Cloud storage data is made accessible for analytics and governance with Dataplex Automatic Discovery.

In a data-driven and AI-driven world, organizations must manage growing amounts of structured and unstructured data. A lot of enterprise data is unused or unreported, called “dark data.” This expansion makes it harder to find relevant data at the correct time. Indeed, a startling 66% of businesses say that at least half of their data fits into this category.

Google Cloud is announcing today that Dataplex, a component of BigQuery’s unified platform for intelligent data to AI governance, will automatically discover and catalog data from Google Cloud Storage to address this difficulty. This potent potential enables organizations to:

Find useful data assets stored in Cloud Storage automatically, encompassing both structured and unstructured material, including files, documents, PDFs, photos, and more.

When data changes, you can maintain schema definitions current with integrated compatibility checks and partition detection to harvest and catalog metadata for your found assets.

With auto-created BigLake, external, or object tables, you can enable analytics for data science and AI use cases at scale without having to duplicate data or build table definitions by hand.

How Dataplex automatic discovery and cataloging works

The following actions are carried out by Dataplex Automatic Discovery and cataloging process:

With the help of the BigQuery Studio UI, CLI, or gcloud, users may customize the discovery scan, which finds and categorizes data assets in your Cloud Storage bucket containing up to millions of files.

Extraction of metadata: From the identified assets, pertinent metadata is taken out, such as partition details and schema definitions.

Database and table creation in BigQuery: BigQuery automatically creates a new dataset with multiple BigLake, external, or object tables (for unstructured data) with precise, current table definitions. These tables will be updated for planned scans as the data in the cloud storage bucket changes.

Preparation for analytics and artificial intelligence: BigQuery and open-source engines like Spark, Hive, and Pig can be used to analyze, process, and conduct data science and AI use cases using the published dataset and tables.

Integration with the Dataplex catalog: Every BigLake table is linked into the Dataplex catalog, which facilitates easy access and search.

Dataplex automatic discovery and cataloging Principal advantages

Organizations can benefit from Dataplex automatic discovery and cataloging capability in many ways:

Increased data visibility: Get a comprehensive grasp of your data and AI resources throughout Google Cloud, doing away with uncertainty and cutting down on the amount of effort spent looking for pertinent information.

Decreased human work: By allowing Dataplex to scan the bucket and generate several BigLake tables that match your data in Cloud Storage, you can reduce the labor and effort required to build table definitions by hand.

Accelerated AI and analytics: Incorporate the found data into your AI and analytics processes to gain insightful knowledge and make well-informed decisions.

Streamlined data access:��While preserving the necessary security and control mechanisms, give authorized users simple access to the data they require.

Please refer to Understand your Cloud Storage footprint with AI-powered queries and insights if you are a storage administrator interested in managing your cloud storage and learning more about your whole storage estate.

Realize the potential of your data

Dataplex’s automated finding and cataloging is a big step toward assisting businesses in realizing the full value of their data. Dataplex gives you the confidence to make data-driven decisions by removing the difficulties posed by dark data and offering an extensive, searchable catalog of your Cloud Storage assets.

FAQs

What is “dark data,” and why does it pose a challenge for organizations?

Data that is unused or undetected in an organization’s systems is referred to as “dark data.” It presents a problem since it might impede well-informed decision-making and represents lost chances for insights.

How does Dataplex address the issue of dark data within Google Cloud Storage?

By automatically locating and cataloguing data assets in Google Cloud Storage, Dataplex tackles dark data and makes them transparent and available for analysis.

Read more on Govindhtech.com

#Dataplex #DataplexAutomatic #CloudStorage #AI #cloudcomputing #BigQuery #BigLaketable #News #Technews #Technology #Technologynews #Technologytrends #govindhtech

0 notes

first-digi-add · 2 years ago

Text

A Beginner's Guide to Google Analytics 4 for 2023

Introduction:

In the ever-evolving world of digital marketing, having access to accurate and insightful data is crucial for making informed decisions. Google Analytics is a powerful tool that provides valuable insights into the performance of your website and online campaigns. With the release of Google Analytics 4 (GA4) in 2020, Google introduced a new era of analytics. In this beginner's guide, we will explore the key features and benefits of GA4, focusing on its relevance and applications in 2023.

Understanding the Basics:

To kickstart our guide, let's begin with an overview of Google Analytics 4 and its fundamental concepts. We'll cover topics such as data collection, events, and the user-centric approach that GA4 adopts.

Key Features of GA4:

In this section, we'll delve into the exciting features that make GA4 stand out from its predecessor, Universal Analytics. We'll explore the enhanced tracking capabilities, the focus on cross-platform measurement, and the incorporation of machine learning for advanced insights. GA4 allows you to track user interactions across multiple platforms, including websites, mobile apps, and offline interactions.

This provides a comprehensive view of your users' journey. For example, a Best Digital Marketing Company in Pune can use GA4 to track and analyze user behavior on a client's website, mobile app, and social media channels, gaining insights into how users interact across different touchpoints.

Setting Up GA4:

Setting up GA4 requires a few steps, and in this section, we'll guide you through the process. We'll cover topics such as creating a new GA4 property, installing the tracking code, and linking GA4 with other Google products.

Navigating the GA4 Interface:

The GA4 interface has been redesigned, and it's essential to familiarize yourself with the new layout and navigation. We'll walk you through the main sections of the GA4 interface and highlight the key reports and metrics you should pay attention to.

Analyzing User Behavior:

One of the primary goals of using Google Analytics is to understand user behavior. In this section, we'll explore how GA4 provides insights into user engagement, conversion tracking, and audience analysis. We'll also discuss the new user-centric reporting approach and how it impacts your analysis.

Leveraging Machine Learning:

GA4 incorporates machine learning algorithms that can provide valuable insights automatically. We'll explore how GA4 uses machine learning to help you understand trends, predict user behavior, and optimize your marketing efforts.

Advanced Features and Integrations:

In this section, we'll dive into some advanced features and integrations available in GA4. We'll discuss custom dimensions and metrics, advanced analysis techniques, and how GA4 integrates with other Google marketing tools like Google Ads and Google BigQuery.

Troubleshooting and FAQs:

No guide is complete without addressing common issues and answering frequently asked questions. We'll address some troubleshooting tips and provide answers to common queries to help you navigate any challenges you may encounter while using GA4.

Conclusion:

Google Analytics 4 represents a significant shift in the world of web analytics, and understanding its capabilities is crucial for digital marketers in 2023. By following this beginner's guide, you'll gain a solid foundation for harnessing the power of GA4 and leveraging its features to make data-driven decisions that drive your digital marketing success. Embrace the opportunities that GA4 offers and unlock valuable insights to optimize your online presence.

#Best Digital Marketing Company in Pune #Best Social Media Marketing Agency #Digital Marketing Agency #Best Social media marketing company in Pune #Best Digital Marketing Company #Digital Marketing Company In India #SEO Services

1 note · View note

pinerbbs · 3 years ago

Text

Ableton live 11 mac keygen

ABLETON LIVE 11 MAC KEYGEN FULL

ABLETON LIVE 11 MAC KEYGEN REGISTRATION

ABLETON LIVE 11 MAC KEYGEN SOFTWARE

We understand you may not agree with this decision, but we hope you'll find alternatives that are just as useful, including BigQuery, Cloud SQL, Maps Platform, and Data Studio. We want to thank all our users these past nine years. Last updated: DecemGoogle Fusion Tables and the Fusion Tables API have been discontinued. FAQ: Google Fusion Tables - Fusion Tables Help. , microsoft project professional 2013 trial product key free, mastercam 2018 failed to initialize com free ,microsoft office starter 2010 freefree. Without interrupting the creative flow, you can start and stop as many real-time audio or MIDI loops as you wish. It enables you to compose, produce, and perform musical compositions.

ABLETON LIVE 11 MAC KEYGEN FULL

Ableton Live Suite Crack v11.2.2 & Full Torrent 2022 Download Ableton Live Suite Crack Download is a digital audio workstation (DAW) for live performance and production.

ABLETON LIVE 11 MAC KEYGEN REGISTRATION

NCH Debut Video Capture Crack v8.40 With Registration Code (2022…. !&p=881f330352ded2acJmltdHM9MTY2MjUwODgwMCZpZ3VpZD0xYWFlNjEyMy0xOWQ2LTY0ZjktMjA3ZC03MzNhMTgwNDY1NWQmaW5zaWQ9NTEyMg&ptn=3&hsh=3&fclid=1aae6123-19d6-64f9-207d-733a1804655d&u=a1aHR0cHM6Ly9tYXJ5YW1qZWUuYmxvZ3Nwb3QuY29tLzIwMjIvMDUvbmF2aWNhdC1wcmVtaXVtLWNyYWNrLTE2MDEzLWZ1bGwta2V5Z2VuLmh0bWw&ntb=1. Without interrupting the creative flow, you can. Navicat Premium Crack 15.0.26 Full Keygen Download. Navicat Premium Crack 16.0.13 Full Keygen Download. Create in a traditional linear arrangement, or improvise without the constraints of a timeline in Live's. It comes with effects, instruments, sounds and all kinds of creative features-everything you need to make any kind of music.

ABLETON LIVE 11 MAC KEYGEN SOFTWARE

Live is fast, fluid and flexible software for music creation and performance.

#Ableton live 11 mac keygen

1 note · View note

weekinethereum · 6 years ago

Text

January 11, 2018

News and Links

Constantinople is coming. [Also, this is the January 11, 2019 issue but I can't fix the title without breaking links]

Upgrade your clients ASAP! EF FAQ and blog post. From MyCrypto, what users need to know about the Constantinople fork

Layer 1

[eth1] Rinkeby testnet forked successfully. Update your clients ASAP!

[eth2] What’s New in Eth2

[eth2] Latest Eth2 implementer call notes

[eth2] Validator economics of Eth2. Also a thorough Eth staking ROI spreadsheet model

[eth2] Discussion about storage rent “eviction archive” nodes and incentives

web3foundation, Status and Validity Labs update and call for participants on private, decentralized messaging, a la Whisper

Layer 2

Live on Rinkeby testnet: Plasma Ignis - often called “roll up” - 500 transactions per second using SNARKs for compression (not privacy), no delay to exit, less liveness requirements, multi-operator. Check out the live demo.

Georgios Konstantopoulos: A Deep Dive on RSA Accumulators

Canto: proposed new subprotocol to allow sidechain-like subnets

Fae: a subnet by putting Fae’s binary transactions in the data field

A RaidenNetwork deep dive explainer

Can watchtowers and monitoring services scale?

Counterfactual dev update: full end to end implementation of Counterfactual with demos and dev environment will be live on Ropsten in next 2 weeks

Stuff for developers

Embark v4.0.0-beta.0

Ganache v2.0.0-beta.2

ZeppelinOS v2.1

Updated EthereumJS readthedocs

Solidity CTF: mirror madness from authio

Solstice: 15 analyzer Solidity security tool

EVM code fuzzing using input prediction

Compound’s self-liquidation bug

Gas Stations Network, an incentivized meta transaction relay network, live on Ropsten

Understanding Rust lifetimes

How to quickly deploy to Görli cross-client testnet

Maker CDP leverager in one call

Codefund2.0 - sustainability for open source project advertising without 3rd party trackers

RSA accumulator in Vyper

Analyzing 1.2m mainnet contracts in 20 seconds using Eveem and BigQuery

0x Market Maker program. 15k to run a market making bot on a 0x relayer

POANet: Honey Badger BFT and Threshold Cryptography

Ecosystem

Afri’s Eth node configuration modes cheat sheet. A great accompaniment to Afri’s did Ethereum reach 1 tb yet? The answer is obviously no, state plus chaindata is about 150 GB.

MyEtherWallet v5 is in beta and MEWConnect on Android

Ethereum Foundation major grant to Parity: $5m for ewasm, light wallet, and Eth2

Enterprise

What enterprises need to know about AWS’s Blockchain as a Service

2019 is the year of enterprise tokens?

Governance and Standards

Notes from latest core devs call, includes ProgPoW section. On that topic, IfDefElse put out a ProgPoW FAQ including responses from AMD and Nvidia. Also check understanding ProgPoW from a few months ago

Martin Köppelmann on the governance protocol of DXdao

Pando Network: DAOs and the future of content

EIP1682: storage rent

EIP1681: temporal replay protection

ERC1683: URLs with asset and onboarding functionality

ERC1690: Mortability standard

ERC820 Pseudo-introspection Registry Contract is final

ERC1155 multi-token standard to last call

Application layer

Demo testing on Kovan testnet of the Digix governance platform

Brave at 5.5m MAUs, up 5x in 2018. It also got much more stable over the year, and being able to use a private tab with TOR on desktop makes it a must (mobile has been a must for a long time). Here’s my referral code if you haven’t switched yet.

I saw some warnings about tokenized US equity DX.exchange that was in the last newsletter. I have no idea if they are legit or if the warnings are in bad faith but the reason that Szabo’s “trusted third parties are security holes” gets repeated frequently is because it is true. If you choose any cryptoasset that depends on custody of a third party, caveat emptor.

Origin now has editable listings and multiple item support

Nevada counties are storing birth and marriage certificates on Ethereum

Scout unveils its customizable token/protocol explorers for apps, live on Aragon and Livepeer

Veil prediction markets platform built on 0x and Augur launches Jan 15 on mainnet. Fantastic to see the app layer stack coming together. Not open to the USA because…federal government.

Gnosis on the problem of front running in dexes

Status releases desktop alpha, v0.9

Interviews, Podcasts, Videos, Talks

Joseph Lubin on Epicenter. Some good early Eth history here.

Curation Markets community call

Ryan Sean Adams on the case for Ether as money on POV Crypto

Nice Decrypt Media profile of Lane Rettig

Q&A with Mariano Conti, head of Maker Oracles

Andrew Keys on the American Banker podcast

Austin Griffith 2018 lessons learned talk at Ethereum Boulder

Starkware’s Eli Ben-Sasson and Alessandro Chiesa on Zero Knowledge

Nick Johnson talks ENS and ProgPoW on Into the Ether

Tokens / Business / Regulation

Paul Kohlhaas: bonding curve design parameters

Ryan Zurrer: Network keepers, v2

Zastrin to sell a tradeable NFT as a license to use its blockchain dev courses.

Sharespost says it did its first compliant security token trade of BCAP (Blockchain Capital). Link opens PDF

Actus Financial Protocol announces standard for tokenizing all financial instruments.

Missing DeFi piece: longer-term interest generating assets

Gemini’s rules for the revolution on working with regulators.

Blockchain Association proposes the Hinman Standard for cryptoassets

Blockchains LLC releases its 300 page Blockchain Through a Legal Lens

China released restrictive blockchain rules including censorship and KYC

Why Ether is Valuable

General

ETC got 51% attacked. Coinbase was first to announce it, though it appears the target was the gate.io exchange. Amusingly, the price hardly suffered. The amazing thing is that a widely known and relatively easily exploited attack vector like this didn’t happen during bull market when this attack could have been an order of magnitude more profitable.

Michael del Castillo tracks the supply chain of an entire dinner using blockchain products like Viant

Julien Thevenard argues Ethereum is on par or safer than Bitcoin in terms of proof of work.

Coindesk video interview of the creator of HODL. He isn’t at all convinced by Bitcoin’s new “store of value” meme. Very entertaining use of 8 minutes.

That very odd Bitcoin nonce pattern. Phil Daian says it is caused by AntMiners

Researchers brute force attack private keys of poorly implemented ECDSA nonce generation.

Dates of Note

Upcoming dates of note (new in bold):

Jan 14 - Mobi Grand Challenge hackathon ends

Jan 10-Feb7 - 0x and Coinlist virtual hackathon

Jan ~16 - Constantinople hard fork at block 7080000

Jan 24 - List of things for Aragon vote, including on funding original AragonOne team

Jan 25 - Graph Day (San Francisco)

Jan 29-30 - AraCon (Berlin)

Jan 31 - GörliCon (Berlin)

Feb 7-8 - Melonport’s M1 conf (Zug)

Feb 15-17 - ETHDenver hackathon (ETHGlobal)

Mar 4 - Ethereum Magicians (Paris)

Mar 5-7 - EthCC (Paris)

Mar 8-10 - ETHParis (ETHGlobal)

Mar 27 - Infura end of legacy key support (Jan 23 begins Project ID prioritization)

April 8-14 - Edcon hackathon and conference (Sydney)

Apr 19-21 - ETHCapetown (ETHGlobal)

May 10-11 - Ethereal (NYC)

If you appreciate this newsletter, thank ConsenSys

This newsletter is made possible by ConsenSys.

I own Week In Ethereum. Editorial control has always been 100% me.

If you're unhappy with editorial decisions or anything that I have written in this issue, feel free to tweet at me.

Housekeeping

Archive on the web if you’re linking to it: http://www.weekinethereum.com/post/181942366088/january-11-2018

Cent link for the night view: https://beta.cent.co/+81o82u

https link: Substack

Follow me on Twitter, because most of what is linked gets tweeted first: @evan_van_ness

If you’re wondering “why didn’t my post make it into Week in Ethereum?”

Did you get forwarded this newsletter? Sign up to receive the weekly email

#Ethereum #blockchain #crypto #Cryptocurrency

1 note · View note

evanvanness · 5 years ago

Text

Annotated edition of May 3 Week in Ethereum News

As it is wont to do, the newsletter buried the lede: ProgPoW is indefinitely shelved.

I think it’s been relatively clear since last time that ProgPoW wasn’t going to happen. The leads of the two largest clients are against it personally, plus it’s quite clear that there isn’t anything close to community consensus. If anything, at the moment the majority of the community opposes it. Greg Colvin bringing it up again last week unfortunately made it harder to do in the case where we do actually need it, ie an ASIC manufacturer has a 10x breakthrough but is only selling the machines privately to control 50%+ of the network.

I’d say it’s unclear whether ACD continues to be a thing. To me it feels like an experiment which was worth trying but has become calcified, which needs a complete refresh in terms of both process and non-technical people involved. But inertia is also a very strong force. To overcome that, Ethereum should have a strong culture of continuously sunsetting things if they are not working.

One amusing thing to me has been the idea that ProgPoW is an AMD/Nvidia conspiracy. Given that ETH price declining in 2018 absolutely destroyed their earnings and share price, those two should have been conspiring! Yet if they were, then they did an exceptionally bad job at it. Instead everyone I know got the impression that the GPU manufacturers were indifferent. There are some competing interests for them of course - the anger of their traditional gaming market, plus AI/neural net researchers - but it still surprises me how they did not get involved at all.

Despite the noise, Ethereum governance works! I remember polling everyone I talked to at EthDenver2019 about whether they supported ProgPoW and (at the time I was pro-ProgPoW; I’d say my position is much more complicated now) being disappointed at how everyone I talked to was against it.

I’m very glad we don’t have on-chain governance where a few exchanges/whales could collude to push things through. Because of that, I’d say on-chain governance will drastically limit the market cap of any basechain’s native token.

Eth1

Latest core devs call. Tim Beiko’s notes. Updates on EIPs for eth2 curve, EVM subroutines. ProgPoW shelved due to clear lack of consensus. Discussion of migrating to binary trie

Analysis of EIP-2315 simple EVM subroutines

DHT+SkipGraph for chain and state data retrieval

Notes from the fee market change call

Vitalik’s EIP1559 fee market change FAQ

There’s a risk of being repetitive, but much of the eth1 work does not lend itself to high-level summaries. Folks are discussing the technical details of EVM improvements (eg, subroutines), as well as getting clients to be stateless (eg the DHT and Skipgraph link). And we’re also talking through EIP1559 in light of Dan Finlay’s escalator algo alternative proposal.

One development not mentioned is that Martin Swende has come around to Alexey’s gas/oil proposal instead of his previous approach of penalties for trie misses.

Eth2

Latest what’s new in Eth2

Schlesi multi-client testnet launched with Lighthouse and (slightly updated) Prysmatic clients. Then Nimbus joined Schlesi a few days later.

Bitfly has a Schlesi explorer

Nimbus client update – up to date, joining Schlesi testnet, RFP for security audits, and benchmarking Nimbus on a 2018 midrange phone

Update from ConsenSys’s TXRX team: prkl network monitoring tool, verifiable precompiles, cross-shard tx simulator, fork choice testing, discv5 sim, and work on turning off proof of work.

A step-by-step guide on joining Prysmatic’s Topaz testnet for Windows10 and MacOS

ConsenSys’s high-level eth2 FAQ

I don’t really do corrections in the newsletter, because once you send an email, you can’t easily clarify your language without sending another email.

But, if you click the “Nimbus joined Schlesi,” then it appears to me that Nimbus is receiving the blocks and following the chain, but not proposing/attesting/etc. I probably should have been more clear when I said “joined.”

Layer2

Channels funding channels: how state channels reduce latency and onchain transactions

This series feels to me like a “yes, state channels are almost here now, let’s get ready to reconsider how to use them.” Productionizing any new technology isn’t easy, and finding the uses that best fit the tradeoffs is not trivial. Seems like this is that series.

This newsletter is made possible by Chainlink

Decentralized oracles are a key capability enabling smart contracts to reach their full potential. Come work with the leading team providing oracles for Ethereum. Join us to help build the next generation of smart contracts in roles including Software Engineering, Developer Evangelism, DevOps, Product Management, and more.

I’m very excited that Week in Ethereum News will continue for the next year due to Chainlink, Celer, Trail of Bits, and 0x.

Stuff for developers

buidler v1.3 – test time-based cases in Buidler EVM, works with TheGraph

Waffle’s plan for making testing better with v3

Testing with Python and Brownie

Typechain v2 – Typescript bindings. truffle v5 support, natspec

Solidity docgen v0.5 – documentation generation for Solidity project

Running async/await scripts in Remix IDE

Austin Griffith’s scaffold-eth, a toolkit to prototype and win hackathons

A linked hashmap in Solidity

How to add proxy Ethereum addresses to BigQuery

Authereum’s batched transactions API for interest rate arbs

discv5 feasibility study for Status

Tutorial to testing on mainnet fork with Ganache, Jest and Uniswap

Etheroll security issue: hacker monitoring for onchain forks and then uses that info to frontrun transactions. Novel (to me!) hack

Dragonfly releases an oracles tracker

Synthetix CTO Justin Moses on 10 things they did to improve their Ethereum development experience. tldr: Buidler, Slither, TheGraph, and Tenderly.

It feels like a very undercommented trend how most devs now tell me that their stack is Buidler + Waffle + ethers, and increasingly Typescript as well. Of course, dev tool stacks are perpetually in flux, but this seems to be the stack du jour.

This isn’t new either. After writing the paragraph above, I remembered that Connext’s Rahul had written something about a similar stack 3 months ago. I go back and check Rahul’s recommendation: Buidler + Waffle + Ethers + typescript. If this was a chatbox, I would put a rofl emoji, but in prose this seems less appropriate.

Ecosystem

Contribute to the TornadoCash trusted setup ceremony. It takes about 5 secs of clicking and requires you to leave the browser tab open a few minutes.

Multisigs controlling multisigs: Avsa’s vision for a usable web3

Renew your ENS names or you will lose them. Names start to expire May 4th

Forgive me the clickbait - you actually have 90 days grace period if your domain expired, but I don’t want anyone to miss this if their domain has expired.

If you haven’t contributed to Tornado’s trusted setup ceremony, I recommend that you do. Assuming that the software works correctly, you can ensure that Tornado becomes trustless for you by participating! It literally takes just a few seconds to start, and then you leave your browser tab open for about 3 minutes. You can even contribute multiple times.

Enterprise

Hyperledger Besu v1.4.4, added priv_getLogs, added Splunk integration

Governance, DAOs, and standards

Governance processes for Maker and Compound add WBTC to Maker and USDT to Compound. TBTC also proposed for Maker

Maker’s MIPs ratification vote is live

MetaClan: DAOs for in-game coordination

ERC2611: Geotimeline Contact Tracing Data Standard

Last call: ERC1363 Payable Token

Last call: EIP1193 Eth provider Javascript API

ERC 2612: permit, 712-signed approvals

EIP2357: Total difficulty in block header

Lots of blowback to Maker adding WBTC. I very much understand the criticism, but to me it looks like Maker is taking reasonable measures, given the current situation where DAI is trading a little rich on the peg. It’s true that permissioned assets have some risk, but this is literally why MKR is supposed to have value: because those MKR holders make good decisions.

Now perhaps you don’t like that model, and that also makes sense, designing for stablecoins is a large solution space. But this has always been the Maker vision. And I say this as someone who does not hold any MKR, and never has (though you’re welcome to give me some!).

Application layer

DeFiZap and DeFiSnap merged to be ZapperFi: now track and trade your DeFi together

Gnosis Safe apps: interact with apps straight from the Gnosis Safe interface

dforce/lendfme plan post-hack: user airdrop, dSAFU insurance fund, large bug bounty

OpenBazaar now supports Eth

A rough proposal for a GasToken forward

Everest: a project registry from TheGraph and MetaCartel

I know I have said this before, but the ebb and flow between sections is fascinating to me. The stuff for devs section was full this week, but the app layer was a little light. Maybe I just missed stuff.

Arbitrary “how much of this section is DeFi” count: 3/6

Tokens/Business/Regulation

UMA did an Initial Uniswap Offering, and there was a 5-10x spike

It appears Telegram will have to return $1.2 billion to investors

Ideo’s Simple Agreement for Future Governance for DeFi

Auditing the 10k top Eth addresses: ETH is better distributed than BTC and a bunch of other interesting claims

I again note that US federal regulators continue to bailout Silicon Valley investors from the worst deals that Silicon Valley did in late 2017/early 2018.

I’d say it’s inevitable that we’re going to see some folks copy UMA. Watch for it.

Adam Cochran’s onchain activity of top 10k addresses is very interesting. Definitely some undersupported claims in there, but certainly worth a read. This is the second time he wrote a 100+ tweetstorm and then compiled it to a blog post. Personally I prefer viewing it as a blog post.

General

EtherScan Connect: an alpha for mapping addresses with a leaderboard

a16z raises $515m crypto fund

Vitalik’s review of Gitcoin grants round 5

SuperMarlin: no trusted setup with DARK polynomial commitment

“alpha for mapping addresses with a leaderboard“ is another thing I could have said more eloquently. It’s an interesting attempt by Etherscan to give something to their community, though of course it comes with risks.

There’s something amusing about a16z announcing a new fund, mentioning Bitcoin, and then mostly talking about the stuff that’s being built on Ethereum, without actually mentioning Ethereum. People like to talk about being contrarian investors. Wanna know how buying ETH is somehow still a contrarian play in crypto right now? It’s right there.

zk continues to just explode. It almost seems like plug and play, where people are pulling out the parts of different schemes that they like and putting in others, depending on the tradeoffs you want around trusted setups, verifier time, prover cost, etc.

Housekeeping

First issue post-ConsenSys. As a reminder, this newsletter is and has always been 100% owned by me.

Did you get forwarded this newsletter? Sign up to receive it weekly

Permalink: https://weekinethereumnews.com/week-in-ethereum-news-may-3-2020/

Dates of Note

Upcoming dates of note (new/changes in bold):

May 6-20 – Gitcoin’s virtual hackthon

May 8-9 – Ethereal Summit (NYC)

May 22-31 – Ethereum Madrid public health virtual hackathon

May 29-June 16 – SOSHackathon

June 17 – EthBarcelona R&D workshop

0 notes

hireindianpvtltd · 6 years ago

Text

Fwd: 🔔 New Content Alert! 🔔 ITIL(R) 4, Microsoft 365 Tenant, Jenkins, TOGAF(R) 9.1, & more...

New Post has been published on https://www.hireindian.in/fwd-%f0%9f%94%94-new-content-alert-%f0%9f%94%94-itilr-4-microsoft-365-tenant-jenkins-togafr-9-1-more/

Fwd: 🔔 New Content Alert! 🔔 ITIL(R) 4, Microsoft 365 Tenant, Jenkins, TOGAF(R) 9.1, & more...

Thanks and Regards

Srinivas

———- Forwarded message ——— From: Alisha from Cloud Academy <[email protected]> Date: Wed, Oct 2, 2019 at 12:33 PM Subject: 🔔 New Content Alert! 🔔 ITIL® 4, Microsoft 365 Tenant, Jenkins, TOGAF® 9.1, & more… To: <[email protected]>

Whether you are looking for training on AWS, Azure, DevOps, Google, Kubernetes, Python, or Security, we have new content just for you!

Not rendering correctly? View this email as a web page here.

Here's what's new…

Hi Srinivas,

Based on your feedback, we released some new features to help make it easier for you to continue studying.

Remove content from “Continue Studying” section

Discard a started quiz without impacting your score

Maintain fullscreen mode when you go to the next lecture

Add training to your calendar

To read more about these new features, go to our blog. Check out how easy it is to add training to your calendar.

What's new:

In September, we released a bunch of other new Learning Paths, Courses, Hands-on Labs, and Lab Challenges. Here are the highlights.

AWS

Course: Developing Serverless ETL with AWS Glue

>>Go to AWS Training Library

Azure

Course: Intro to Planning Office 365 Workloads and Applications

Course: Setting up and Managing a Microsoft 365 Tenant

Hands-on Lab: Create and Configure Load Balancers in Microsoft Azure

Hands-on Lab: Deploy and Modify Azure Resource Manager Templates

Lab Challenge: Microsoft Azure Administrator AZ-103 Challenge

>>Go to Azure Training Library

Containers

Hands-on Lab: Introduction to Kubernetes Playground

>>Go to Containers Library

DevOps

Learning Path: Combining DevOps Tools at Scale – Jenkins, Sonarcube, Artifactory, Splunk, and Jira

Course: Jenkins CICD – Advanced

>>Go to DevOps Library

IT Fundamentals

Learning Path: ITIL 4 Foundation in IT Service Management

TOGAF 9.1 Foundation and Certified Level 1 and 2

>>Go to IT Fundamentals Library

Google Cloud Platform

Hands-on Lab: Create a Network Infrastructure with Google Virtual Private Cloud

Hands-on Lab: Structure and Analyze Data with Google BigQuery

>>Go to Google Library

Kubernetes

Hands-on Lab: Introduction to Kubernetes Playground

>>Go to Kubernetes Library

Python

Lab Challenge: Python for Beginners

>>Go to Python Library

Learn the "right" way to measure training outcomes

Don't miss our webinar, The Right Way to Measure Training Programs: Skill Outcomes are More Important Than Content Consumption, on October 3 at 10 a.m. PT. to gain insights into:

Why strict content consumption data ultimately leaves you empty-handed

How and why skills can be measured for leadership

How the process works, from implementation to continual assessment

>>Sign up

Stay updated

As always, we use Cloud Academy Blog to keep you up-to-date on the latest technology and industry best practices. All of our new blogs, reports, and updates are posted directly on our Cloud Academy social media accounts. For the latest updates, follow and like us on the following social media platforms:

YouTube

Facebook

Twitter

Thanks for being part of the community,

Alisha | Cloud Academy

Cloud Academy 1 Bluxome Street #418 | San Francisco, CA 94107

Getting too many updates from Cloud Academy? Adjust your preferences here.

0 notes

android-for-life · 7 years ago

Text

"What a week! 105 announcements from Google Cloud Next '18"

Google Cloud Next ‘18 was incredible! From fantastickeynotes and fireside chats to GO-JEK CTO Ajey Gore appearing on-stage on a scooter to listening to Target CIO Mike McNamara we had an inspiring, educational and entertaining week at our flagship conference. We were joined by over 23,000 leaders, developers and partners from our Google Cloud community, listened to more than 290 customer speakers share their stories of business transformation in the cloud and took part in hundreds of breakout sessions. The theme of the conference was Made Here Together, and we’re so grateful to everyone who attended and contributed to help build the cloud for everyone.

But the week of Next wouldn’t be complete without a comprehensive list of what happened. So without further ado, here are 105 product and solution launches, customer stories and announcements from Next ‘18.

Customers

eBay—The world’s largest global marketplace is leveraging Google Cloud in many different ways, including experimenting with conversational commerce with Google Assistant, building ML models with Cloud TPUs for image classification, and applying AI to help buyers quickly find what they’re looking for.

GO-JEK—This ride-hailing and logistics startup in Jakarta uses Google Cloud to support its hundreds of thousands of concurrent transactions, Maps for predicting traffic and BigQuery to get data insights.

Lahey Health—Lahey’s journey to the cloud included migrating from four legacy email systems to G Suite in 91 days.

LATAM Airlines—South America’s largest airline uses G Suite to connect teams, and GCP for data analytics and creating 3D digital elevation models.

LG CNS—LG is looking to Google Cloud AI, Cloud IoT Edge and Edge TPU to build its Intelligent Vision inspection tool for better quality and efficiency in some of its factories.

HSBC—One of the world’s leading banking institutions shares how they’re using data analytics on Google Cloud to extract meaningful insights from its 100PB of data and billions of transactions.

The New York Times—The newest way the New York Times is using Google Cloud is to scan, encode, and preserve its entire historical photo archive and evolve the way the newsroom tells stories by putting new tools for visual storytelling in the hands of journalists.

Nielsen—To support its nearly 45,000 employees in 100 countries with real-time collaboration and cost-effective video conferencing, Nielsen turned to G Suite.

Ocado—This online-only supermarket uses Google Cloud’s AI capabilities to power its machine learning model for responding to customer requests and detecting fraud much faster.

PayPal—PayPal discusses the hows and whys of their journey to the public cloud.

Scotiabank—This Canadian banking institution shares its views on modernizing and using the cloud to solve inherent problems inside an organization.

Sky—The UK media company uses Google Cloud to identify and disconnect pirate streaming sites during live sporting events.

Target—Moving to Google Cloud has helped Target address challenges like scaling up for Cyber Monday without disruptions, and building new, cutting-edge experiences for their guests.

20th Century Fox—The renowned movie studio shares how it’s using BigQuery ML to understand audience preferences.

Twitter—Twitter moved large-scale Hadoop clusters to GCP for ad hoc analysis and cold storage, with a total of about 300 PB of data migrated.

Veolia—This environmental solution provider moved its 250 systems to G Suite for their anytime, anywhere, any-device cloud project.

Weight Watchers—How Weight Watchers evolved its business, including creating mobile app and an online community to support its customers’ lifestyles.

Partners

2017 Partner Awards—Congratulations to the winners! These awards recognize partners who dedicated themselves to creating industry-leading solutions and strong customer experiences with Google Cloud.

SAP and Deloitte collaboration—Customers can run SAP apps on GCP with Deloitte’s comprehensive tools.

Updates to our Cisco partnership—Includes integrations between our new Call Center AI solution and Cisco Customer Journey solutions, integrations with Webex and G Suite, and a new developer challenge for hybrid solutions.

Digital Asset and BlockApps—These launch partners are helping users try Distributed Ledger Technology (DLT) frameworks on GCP, with open-source integrations coming later this year.

Intel and Appsbroker—We’ve created a cloud center of excellence to make high-performance cloud migration a lot easier.

NetApp—New capabilities help customers access shared file systems that apps need to move to cloud, plus Cloud Volumes are now available to more GCP customers.

VMware vRealize Orchestrator—A new plug-in makes it easy to use GCP alongside on-prem VMware deployments for efficient resource provisioning.

New partner specializations—We’ve recently welcomed 19 partners in five new specialization areas (bringing the total areas to nine) so customers can get even more industry-specific help moving to cloud.

SaaS-specific initiative—A new set of programs to help our partners bring SaaS applications to their customers.

Accenture Google Cloud Business Group, or AGBG—This newly formed group brings together experts who’ll work with enterprise clients to build tailored cloud solutions.

Partnership with NIH—We’re joining with the National Institutes of Health (NIH) to make more research datasets available, integrate researcher authentication and authorization mechanisms with Google Cloud credentials, and support industry standards for data access, discovery, and cloud computation.

Partnership with Iron Mountain—This new partnership helps enterprises extract hard-to-find information from inside their stored documents.

Chrome, Devices and Mobility

Cloud-based browser management—From a single view, admins can manage Chrome Browser running on Windows, Mac, Chrome OS and Linux.

Password Alert Policy—Admins can set rules to prevent corporate password use on sites outside of the company’s control.

Managed Google Play (out of beta)—Admins can curate applications by user groups as well as customize a broad range of policies and functions like application blacklisting and remote uninstall.

Google Cloud Platform | AI and machine learning

Cloud AutoML Vision, AutoML Natural Language, and AutoML Translation (all three in beta)—Powerful ML models that can be extended to suit specific needs, without requiring any specialized knowledge in machine learning or coding.

Cloud Vision API (GA)—Cloud Vision API now recognizes handwriting, supports additional file types (PDF and TIFF), and can identify where an object is located within an image.

Cloud Text-to-Speech (beta)—Improvements to Cloud Text-to-Speech offer multilingual access to voices generated by DeepMind WaveNet technology and the ability to optimize for the type of speaker you plan to use.

Cloud Speech-to-Text—Updates to this API help you identify what language is being spoken, plus provide word-level confidence scores and multi-channel (multi-participant) recognition.

Training and online prediction through scikit-learn and XGBoost in Cloud ML Engine (GA) —While Cloud ML Engine has long supported TensorFlow, we’re releasing XGBoost and scikit-learn as alternative libraries for training and classification.

Kubeflow v0.2—Building on the previous version, Kubeflow v0.2 makes it easier for you to use machine learning software stacks on Kubernetes. Kubeflow v0.2 has an improved user interface and several enhancements to monitoring and reporting.

Cloud TPU v3 (alpha)—Announced at this year’s I/O, our third-generation TPUs are now available for Google Cloud customers to accelerate training and inference workloads.

Cloud TPU Pod (alpha)—Second-generation Cloud TPUs are now available to customers in scalable clusters. Support for Cloud TPUs in Kubernetes Engine is also available in beta.

Phone Gateway in Dialogflow Enterprise Edition (beta)—Now you can assign a working phone number to a virtual agent—all without infrastructure. Speech recognition, speech synthesis, natural language understanding and orchestration are all managed for you.

Knowledge Connectors in Dialogflow Enterprise Edition (beta)—These connectors understand unstructured documents like FAQs or knowledge base articles and complement your pre-built intents with automated responses sourced from internal document collections.

Automatic Spelling Correction in Dialogflow Enterprise Edition (beta)—Natural language understanding can sometimes be challenged by spelling and grammar errors in a text-based conversation. Dialogflow can now automatically correct spelling mistakes using technology similar to what’s used in Google Search and other products.

Sentiment Analysis in Dialogflow Enterprise Edition (beta)—Relies on the Cloud Natural Language API to optionally inspect a request and score a user's attitude as positive, negative or neutral.

Text-to-Speech in Dialogflow Enterprise Edition (beta)—We’re adding native audio response to Dialogflow to complement existing Speech-to-Text capability.

Contact Center AI (alpha)—A new solution which includes new Dialogflow features alongside other tools to perform analytics and assist live agents.

Agent Assist in Contact Center AI (alpha)—Supports a live agent during a conversation and provides the agent with relevant information, like suggested articles, in real-time.

Conversational Topic Modeler in Contact Center AI (alpha)—Uses Google AI to analyze historical audio and chat logs to uncover insights about topics and trends in customer interactions.

Google Cloud Platform | Infrastructure services

Managed Istio (alpha)—A fully-managed service on GCP for Istio, an open-source project that creates a service mesh to manage and control microservices.

Istio 1.0—Speaking of open-source Istio, the project is imminently moving up to version 1.0.

Apigee API Management for Istio (GA)—Soon you can use your existing Apigee Edge API management platform to wrangle microservices running on the Istio service mesh.

Stackdriver Service Monitoring (early access)—A new view for our Stackdriver monitoring suite that shows operators how their end users are experiencing their systems. This way, they can manage against SRE-inspired SLOs.

GKE On-Prem with multi-cluster management (coming soon to alpha)—A Google-configured version of Kubernetes that includes multi-cluster management and can be deployed on-premise or in other clouds, laying the foundation for true hybrid computing.

GKE Policy Management (coming soon to alpha)—Lets you take control of your Kubernetes environment by applying centralized policies across all enrolled clusters.

Resource-based pricing for Compute Engine (rolling out this fall)—A new way we’re calculating sustained use discounts on Compute Engine machines, aggregating all your vCPUs and memory resources to maximize your savings.

Google Cloud Platform | Application development

GKE serverless add-on (coming soon to alpha)—Runs serverless workloads that scale up and down automatically, or respond to events, on top of Kubernetes Engine.

Knative—The same technologies included in the GKE serverless add-on are now available in this open-source project.

Cloud Build (GA)—Our fully managed continuous integration and continuous delivery (CI/CD) platform lets you build container and non-container artifacts and integrates with a wide variety of tools from across the developer ecosystem.

GitHub partnership—GitHub is a popular source code repository, and now you can use it with Cloud Build.

New App Engine runtimes—We’re adding support for the popular Python 3.7 and PHP 7.2 runtimes to App Engine standard environment.

Cloud Functions (GA)—Our event-driven serverless compute service is now generally available, and includes support for additional languages, plus performance, networking and security features.

Serverless containers on Cloud Functions (early preview)—Packages a function within a container, to better support custom runtimes, binaries and frameworks.

Google Cloud Platform | Data analytics

BigQuery ML (beta)—A new capability that allows data analysts and data scientists to easily build machine learning models directly from BigQuery with simple SQL commands, making machine learning more accessible to all.

BigQuery Clustering (beta)—Creates clustered tables in BigQuery as an added layer of data optimization to accelerate query performance.

BigQuery GIS (public alpha)—New functions and data types in BigQuery that follow the SQL/MM Spatial standard. Handy for PostGIS users and anyone already doing geospatial analysis in SQL.

Sheets Data Connector for BigQuery (beta)—A new way to directly access and refresh data in BigQuery from Google Sheets.

Data Studio Explorer (beta)—Deeper integration between BigQuery and Google Data Studio to help users visualize query results quickly.

Cloud Composer (GA)—Based on the open source Apache Airflow project, Cloud Composer distributes workloads across multiple clouds.

Customer Managed Encryption Keys for Dataproc—Customer-managed encryption keys that let customers create, use and revoke key encryption for BigQuery, Compute Engine and Cloud Storage. Generally available for BigQuery; beta for Compute Engine and Cloud Storage.

Streaming analytics updates, including Python Streaming and Dataflow Streaming Engine (both in beta)—Provides streaming customers more responsive autoscaling on fewer resources, by separating compute and state storage.

Dataproc Autoscaling and Dataproc Custom Packages (alpha)—Gives users Hadoop and Spark clusters that scale automatically based on the resource requirements of submitted jobs, delivering a serverless experience.

Google Cloud Platform | Databases

Oracle workloads on GCP—We’re partnering with managed service providers (MSPs) so you can run Oracle workloads on GCP using dedicated hardware.

Compute Engine VMs powered by Intel Optane DC Persistent Memory—Lets you run SAP HANA workloads for more capacity at lower cost.

Cloud Firestore (beta)—Helps you store, sync and query data for cloud-native apps. Support for Datastore Mode is also coming soon.

Updates to Cloud Bigtable—Regional replication across zones and Key Visualizer, in beta, to help debug performance issues.

Updates to Cloud Spanner—Lets users import and export data using Cloud Dataflow. A preview of Cloud Spanner’s data manipulation language (DML) is now available.

Resource-based pricing model for Compute Engine—A new billing model gives customers more savings and a simpler bill.

Google Cloud Platform | IoT

Edge TPU (early access)—Google’s purpose-built ASIC chip that’s designed to run TensorFlow Lite ML so you can accelerate ML training in the cloud and utilize fast ML inference at the edge.

Cloud IoT Edge (alpha)—Extends data processing and machine learning capabilities to gateways, cameras and end devices, helping make IoT devices and deployments smart, secure and reliable.

Google Cloud Platform | Security

Context-aware access—Capabilities to help organizations define and enforce granular access to GCP APIs, resources, G Suite, and third-party SaaS apps based on a user’s identity, location and the context of their request.

Titan Security Key—A FIDO security key that includes firmware developed by Google to verify its integrity.

Shielded VMs (beta)—A new way to leverage advanced platform security capabilities to help ensure your VMs haven’t been tampered with or compromised.

Binary Authorization (alpha)—Lets you enforce signature validation when deploying container images.

Container Registry Vulnerability Scanning (alpha)—Automatically performs vulnerability scanning for Ubuntu, Debian and Alpine images to help ensure they are safe to deploy and don’t contain vulnerable packages.

Geo-based access control in Cloud Armor (beta)—Lets you control access to your services based on the geographic location of the client trying to connect to your application.

Cloud HSM (alpha)—A fully managed cloud-hosted hardware security module (HSM) service that allows you to host encryption keys and perform cryptographic operations in FIPS 140-2 Level 3 certified HSMs.

Access Transparency (coming soon to GA)—Provides an audit trail of actions taken by Google Support and Engineering in the rare instances that they interact with your data and system configurations on Google Cloud.

G Suite | Enterprise collaboration and productivity

New investigation tool in the Security Center (Early Adopter Program)—A new tool in the security center for G Suite that helps admins identify which users are potentially infected, see if anything’s been shared externally and remove access to Drive files or delete malicious emails.

Data Regions for G Suite (available now for G Suite Business and Enterprise customers)—Lets you choose where to store primary data for select G Suite apps—globally, distributed, U.S. or Europe.

Smart Reply in Hangouts Chat—Coming soon to G Suite, Smart Reply uses artificial intelligence to recognize which emails need responses and proposes reply options.

Smart Compose in Gmail—Coming soon to G Suite, Smart Compose intelligently autocompletes emails for you by filling in greetings, common phrases and more.

Grammar Suggestions in Google Docs (Early Adopter Program)—Uses a unique machine translation-based approach to recognize grammatical errors (simple and complex) and suggest corrections.

Voice Commands for Hangouts Meet hardware (coming to select Hangouts Meet hardware customers later this year)—Brings some of the same magic of the Google Assistant to the conference room so that teams can connect to video meetings quickly.

The new Gmail (GA)—Features like redesigned security warnings, snooze and offline access are now generally available to G Suite users.

New functionality in Cloud Search—Helps organizations intelligently and securely index third-party data beyond G Suite (whether the data is stored in the cloud or on-prem).

Google Voice to G Suite (Early Adopter Program)—An enterprise version of Google Voice that lets admins manage users, provision and port phone numbers, access detailed reports and more.

Standalone offering of Drive Enterprise (GA)—New offering with usage-based pricing to help companies easily transition data from legacy enterprise content management (ECM) systems.

G Suite Enterprise for Education—Expanding to 16 new countries.

Jamboard Mobile App—Added features for Jamboard mobile devices, including new drawing tools and a new way to claim jams using near-field communication (NFC).

Salesforce Add-on in Google Sheets—A new add-on that lets you import data and reports from Salesforce into Sheets and then push updates made in Sheets back to Salesforce.

Social Impact

Data Solutions for Change—A program that empowers nonprofits with advanced data analytics to drive social and environmental impact. Benefits include role-based support and Qwiklabs.

Visualize 2030—In collaboration with the World Bank, the United Nations Foundation, and the Global Partnership for Sustainable Development Data, we’re hosting a data storytelling contest for college or graduate students.

Harambee Youth Employment Accelerator—We’re helping Harambee connect more unemployed youth with entry-level positions in Johannesburg by analyzing large datasets with BigQuery and machine learning on Cloud Dataflow.

Foundation for Precision Medicine—We’re aiding the Foundation for Precision Medicine to find a cure for Alzheimer’s disease by scaling their patient database to millions of anonymized electronic medical record (EMR) data points, creating custom modeling, and helping them visualize data.

Whew! That was 104. Thanks to all our customers, partners, and Googlers for making this our best week of the year.

But wait, there’s more! Here’s the 105th announcement: Next 2019 will be April 9-11 at the newly renovated Moscone in San Francisco. Please save the date!

Source : The Official Google Blog via Source information

#jeprog

0 notes

govindhtech · 8 months ago

Text

Boost AI Production With Data Agents And BigQuery Platform

Data accessibility can hinder AI adoption since so much data is unstructured and unmanaged. Data should be accessible, actionable, and revolutionary for businesses. A data cloud based on open standards, that connects data to AI in real-time, and conversational data agents that stretch the limits of conventional AI are available today to help you do this.

An open real-time data ecosystem

Google Cloud announced intentions to combine BigQuery into a single data and AI use case platform earlier this year, including all data formats, numerous engines, governance, ML, and business intelligence. It also announces a managed Apache Iceberg experience for open-format customers. It adds document, audio, image, and video data processing to simplify multimodal data preparation.

Volkswagen bases AI models on car owner’s manuals, customer FAQs, help center articles, and official Volkswagen YouTube videos using BigQuery.

New managed services for Flink and Kafka enable customers to ingest, set up, tune, scale, monitor, and upgrade real-time applications. Data engineers can construct and execute data pipelines manually, via API, or on a schedule using BigQuery workflow previews.

Customers may now activate insights in real time using BigQuery continuous queries, another major addition. In the past, “real-time” meant examining minutes or hours old data. However, data ingestion and analysis are changing rapidly. Data, consumer engagement, decision-making, and AI-driven automation have substantially lowered the acceptable latency for decision-making. The demand for insights to activation must be smooth and take seconds, not minutes or hours. It has added real-time data sharing to the Analytics Hub data marketplace in preview.

Google Cloud launches BigQuery pipe syntax to enable customers manage, analyze, and gain value from log data. Data teams can simplify data conversions with SQL intended for semi-structured log data.

Connect all data to AI

BigQuery clients may produce and search embeddings at scale for semantic nearest-neighbor search, entity resolution, semantic search, similarity detection, RAG, and recommendations. Vertex AI integration makes integrating text, photos, video, multimodal data, and structured data easy. BigQuery integration with LangChain simplifies data pre-processing, embedding creation and storage, and vector search, now generally available.

It previews ScaNN searches for large queries to improve vector search. Google Search and YouTube use this technology. The ScaNN index supports over one billion vectors and provides top-notch query performance, enabling high-scale workloads for every enterprise.

It is also simplifying Python API data processing with BigQuery DataFrames. Synthetic data can replace ML model training and system testing. It teams with Gretel AI to generate synthetic data in BigQuery to expedite AI experiments. This data will closely resemble your actual data but won’t contain critical information.

Finer governance and data integration

Tens of thousands of companies fuel their data clouds with BigQuery and AI. However, in the data-driven AI era, enterprises must manage more data kinds and more tasks.

BigQuery’s serverless design helps Box process hundreds of thousands of events per second and manage petabyte-scale storage for billions of files and millions of users. Finer access control in BigQuery helps them locate, classify, and secure sensitive data fields.

Data management and governance become important with greater data-access and AI use cases. It unveils BigQuery’s unified catalog, which automatically harvests, ingests, and indexes information from data sources, AI models, and BI assets to help you discover your data and AI assets. BigQuery catalog semantic search in preview lets you find and query all those data assets, regardless of kind or location. Users may now ask natural language questions and BigQuery understands their purpose to retrieve the most relevant results and make it easier to locate what they need.

It enables more third-party data sources for your use cases and workflows. Equifax recently expanded its cooperation with Google Cloud to securely offer anonymized, differentiated loan, credit, and commercial marketing data using BigQuery.

Equifax believes more data leads to smarter decisions. By providing distinctive data on Google Cloud, it enables its clients to make predictive and informed decisions faster and more agilely by meeting them on their preferred channel.

Its new BigQuery metastore makes data available to many execution engines. Multiple engines can execute on a single copy of data across structured and unstructured object tables next month in preview, offering a unified view for policy, performance, and workload orchestration.

Looker lets you use BigQuery’s new governance capabilities for BI. You can leverage catalog metadata from Looker instances to collect Looker dashboards, exploration, and dimensions without setting up, maintaining, or operating your own connector.

Finally, BigQuery has catastrophe recovery for business continuity. This provides failover and redundant compute resources with a SLA for business-critical workloads. Besides your data, it enables BigQuery analytics workload failover.

Gemini conversational data agents

Global organizations demand LLM-powered data agents to conduct internal and customer-facing tasks, drive data access, deliver unique insights, and motivate action. It is developing new conversational APIs to enable developers to create data agents for self-service data access and monetize their data to differentiate their offerings.

Conversational analytics

It used these APIs to create Looker’s Gemini conversational analytics experience. Combine with Looker’s enterprise-scale semantic layer business logic models. You can root AI with a single source of truth and uniform metrics across the enterprise. You may then use natural language to explore your data like Google Search.

LookML semantic data models let you build regulated metrics and semantic relationships between data models for your data agents. LookML models don’t only describe your data; you can query them to obtain it.

Data agents run on a dynamic data knowledge graph. BigQuery powers the dynamic knowledge graph, which connects data, actions, and relationships using usage patterns, metadata, historical trends, and more.

Last but not least, Gemini in BigQuery is now broadly accessible, assisting data teams with data migration, preparation, code assist, and insights. Your business and analyst teams can now talk with your data and get insights in seconds, fostering a data-driven culture. Ready-to-run queries and AI-assisted data preparation in BigQuery Studio allow natural language pipeline building and decrease guesswork.

Connect all your data to AI by migrating it to BigQuery with the data migration application. This product roadmap webcast covers BigQuery platform updates.