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shefsolutionllc · 7 months ago

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Shef Solutions LLC's Data Science Bootcamp in San Francisco: Accelerate Your Career

The demand for skilled data scientists is skyrocketing, and San Francisco, the heart of the tech world, is the perfect place to launch or advance your data science career. At Shef Solutions LLC, we’re offering a cutting-edge Data Science Bootcamp in San Francisco that provides hands-on training, expert guidance, and 100% Job Assistance to help you break into the data science field.

Why Join Our Data Science Bootcamp?

Our Data Science Bootcamp is designed to give you an intensive, fast-track learning experience that combines practical skills with real-world applications. Here’s why our bootcamp stands out:

1. Immersive Learning in the Tech Capital By choosing our San Francisco-based bootcamp, you’ll not only learn in one of the world’s top tech hubs, but you’ll also gain access to networking opportunities with leading companies and professionals in the industry.

2. Comprehensive Curriculum We cover everything you need to become a successful data scientist, from the basics to advanced techniques:

Python and R Programming: Master the core programming languages for data science.

Data Wrangling and Cleaning: Learn how to handle messy datasets and prepare them for analysis.

Machine Learning: Build predictive models using supervised and unsupervised learning techniques.

Data Visualization: Communicate insights effectively using tools like Matplotlib, Seaborn, and Tableau.

Big Data and Cloud Computing: Gain proficiency in handling large-scale data with Hadoop, Spark, and cloud platforms.

3. Hands-On Experience with Real-World Projects Throughout the bootcamp, you’ll work on projects that simulate real-world business challenges. From analyzing market trends to building machine learning models, you’ll develop a portfolio that demonstrates your capabilities to future employers.

4. Expert Instructors Learn from industry veterans with years of experience in data science. Our instructors bring their real-world expertise into the classroom, ensuring you gain both theoretical knowledge and practical skills.

100% Job Assistance in San Francisco

At Shef Solutions LLC, we don’t just train you—we ensure you have the support you need to land a job after completing the bootcamp. Our 100% Job Assistance program includes:

Resume Building and Review: We’ll help you create a standout resume that highlights your newly acquired skills.

Interview Preparation: Practice mock interviews with experts to prepare for technical and behavioral questions.

Job Search Support: Get assistance in finding the right job openings, applying to roles, and connecting with recruiters in the San Francisco tech scene.

Who Should Attend?

Career Changers: Whether you're coming from IT, business, or an entirely different field, our bootcamp provides the skills you need to transition into data science.

Recent Graduates: If you’ve just finished college and are looking for a way to break into the tech industry, our bootcamp will give you a competitive edge.

Professionals Seeking to Upskill: Already working in tech or analytics? This bootcamp will help you expand your expertise and move up the career ladder.

Why Choose San Francisco?

San Francisco is home to some of the world’s biggest tech giants and innovative startups, making it an ideal location to start or advance your career in data science. By participating in our

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jonostocker · 6 years ago

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Find the latest Big Data Hadoop Developer In San Francisco that are hiring now. Apply the best Opt Jobs, Careers In San Francisco.

#San Francisco #opt jobs #cpt jobs #Big Data Hadoop Developer In San Francisco

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tristanleggett · 6 years ago

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Wroclaw’s Software Houses Are Making a Statement in IT Outsourcing

We see a very clear trend in the software development space. The top companies use the power of Inbound marketing to grow their customer acquisition and business.

They don’t chase customer, customers chase them.

How did they get here using marketing? They build stellar content about technology and their successful case study.

We’ve done the heavy lifting for you analyzing all the aspects of marketing all the top software companies do to grow.

Sounds simple but sophisticated.

Take these insights, filter them for your business and buyer persona, then implement them in your business.

We’ve learned in our previous blog posts that 3 of the top European companies in software consulting and development are from Poznan, Poland.

And all 3 of them use content marketing and inbound marketing to blast a bunch of relevant traffic to their website using content marketing.

Traffic that converts in customers or future employees.

For our next blog post series, we go South from Poznan.

In our road trip in discovering the marketing strategies of the best software houses in Poland we’ve arrived at Little Venice, Wroclaw.

Here we look at Monterail, Droids on Roids, Divante, Tooploox. Probably it doesn’t ring a bell yet, but they’re on the verge of writing some history in IT outsourcing.

In IT Outsourcing Wroclaw is aiming to lead the way. Can Wroclaw’s IT outsourcing companies cope up with the challenge?

In our 5 blog posts series, we’ll decipher how Wroclaw’s IT Outsourcing companies grow and do marketing, community management, and employer branding.

Let’s uncover their stories together.

TABLE OF CONTENT

Wroclaw’s Assets for a New Era of Growth

Wroclaw's Software Houses

Monterail - Delivering Meaningful Software

Droids on Roids - World-class Software House

Tooploox - We Build Great Products

Divante - eCommerce Software House

Summing Up

I felt a great disturbance in the Force as if millions of voices suddenly cried out in terror and were suddenly silenced - Obi-Wan Kenobi

That’s disruption right there. It’s leaving a mark on every single industry. And if you want to grow your business, you’ll need to embrace change and drive innovation.

IT Outsourcing is no exception.

Wroclaw IT outsourcing companies are turning their backs to old-school ways of doing business.

Come with me on a journey of agony and ecstasy, a journey where we’ll meet the businesses that want to write the future of IT outsourcing.

Wroclaw’s Assets for a New Era of Growth

First, let’s see what makes Wroclaw so sexy in the eyes of IT investors?

Income tax exemptions: regional public aid is granted for supporting new investments and new jobs creation

Nationwide leader in R&D centers: companies that are developing here Atos, BNY Mellon, Credit Suisse, HP, Nokia Solutions, SII, and Volvo

Local talent pool: Wroclaw University of Science and Technology offers students 50+ programs. 45k+ students enrolled in technical subjects in 2015, according to PWC report.

Wroclaw is the most attractive Polish city for relocation, as seen by native Polish employees, especially top specialists and managers. The criteria for this top referred to the aspect of the cities, career opportunities, employer activities, employer-institutions relationships.

Lots of business and tech events (startup weekends, conferences etc)

60+ tech meetup groups, with members ranging from 100 to 1600+

Wroclaw's Software Houses

According to Stratistics, the IT Outsourcing market is expected to reach $481 billion by 2022.

The growth is fueled by new business models and new technologies: cloud computing, VR, AI, blockchain.

In our growth saga, we’ll try to figure out how Wroclaw software houses are moving a needle in IT outsourcing and if they have adapted their software solutions to the new market demands. Also, we’ll unfold their marketing strategies and analyze their employer branding.

Monterail - Delivering Meaningful Software

Website: https://www.monterail.com/

No. employees: 80+

Revenue: 3M+ (Owler estimations)

Technologies: Vue.js, Ruby on Rails, NodeJS, React, AngularJS,

Services: web development, custom software development, mobile app development, product design, IoT development

Verticals: business, healthcare, financial

Key clients: Merck, Solarflare, Cooleaf, Loyco, Gutwin, Tailored, University of Wroclaw, Xchanging, Teambook, WFC, Innovestment

Offices: Wroclaw (HQ)

Reviews: 4.8 - Clutch (13 reviews), 4.7 - Glassdoor (11 reviews)

Co-founders: Szymon Boniecki and Bartosz Rega

Featured two times in Deloitte’s CEE Tech Fast 50 in 2017 and 2016, Monterail is among Wroclaw ’s most dynamic software houses.

In our next blog post of the current series, we’ll go beyond the introduction, we’ll unfold the marketing secrets behind Monterail’s growth and understand how employer branding is built.

We’ll go deep intro content strategies, social media and community engagement.

But, until then, you can take a peek inside Monterail’s company culture here:

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Deloitte recognizes Monterail as one of the fastest growing tech companies in Central Europe

Droids on Roids - World-class Software House

Website: https://www.thedroidsonroids.com/

No. employees: 40+

Technologies: Android, iOS, Node.js, Ruby on Rails, React, MongoDB, Vue.js, Express.js

Services: mobile app development, web development, product design

Verticals: entertainment, business, consumer products and services

Key clients: Giphy, Oh Mi Bod, Skybuds, Loop, Electric Objects, LiveChat, Złote Wyprzedaże, Disney, Nestle, Unilever

Offices: Wroclaw (HQ), London, San Francisco

Reviews: 4.8 - Clutch (20 reviews)

CEO: Wojtek Szwajkiewicz

The company brags with being recognized by Forbes Magazine as one of the fastest growing companies from Poland. Droids On Roids is ranked in 5th place for Poland and 2nd for the Lower Silesia region, in the category “Income between 5-50 mln PLN”.

Their income has increased by 761% over the last 5 years (according to the same Forbes magazine) and they shook hands with big clients such as Nestle, Unilever or Disney.

They organize bootcamps and meetups and strive to build their employer brand.

They invest heavily in content, that’s why their monthly website traffic is around 75k (according to Similar Web), not bad for a B2B, right?

Tooploox - We Build Great Products

Website:https://www.tooploox.com

No. employees: 100+

Revenue: EUR 3M+ (2016, via Financial Times)

Technologies: Android, iOS, Python, React, C++

Services: AI, data science, blockchain, IoT, mobile app development, web development, product design

Verticals: education, tourism, health, e-commerce

Key clients: TEDx, Homebook, Happy Cow, Domodi

Offices: Wroclaw (HQ), Warsaw, Gdansk, Berlin

Reviews: 4.8 - Clutch (3 reviews), 4.6 - Glassdoor (23 reviews)

Co-founders: Pawel Solyga and Damian Walczak

Tooploox ranked 4th in Deloitte’s Technology Fast 50 CEE in 2017 with an impressive 2827% revenue growth.

With a 67% increase in employees in the last 2 years, the company has big plans. Looking at their open job positions Tooploox is embracing the AI future.

This is just a hint of our in depth-analysis, following this blog post. We’ll tackle employee branding, content and social media strategies, and try to figure out what lies behind their inspiring growth.

Furthermore, here’s an interview featuring Tooploox, Droidsonroids and Monterail’s founders/CEOs where you’ll understand their culture and what made these Wroclaw software houses grow.

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Q&A session with the founders of the fastest growing tech companies in Europe according to Deloitte's Technology Fast 50: Monterail, Droids on Roids, Tooploox

Divante - eCommerce Software House

Website: https://divante.co/

No. employees: 150+

Technologies: Magento, Angular, MongoDB, Node.js, Hadoop, Symfony 2, Progressive Web Apps, Modern JS, Vue.js, React

Services: B2B Commerce, eCommerce, Mobile, UX Design, Magento developers, Magento consulting, Magento hosting, Pimcore development, OroCommerce development, Frontend development

Verticals: automotive, energy, financial services, e-commerce, telekom

Key clients: Continental, ING Bank, Tchibo, Intersport, Santander, Knauf, T-Mobile

Offices: Wroclaw (HQ)

Reviews: 4.6 - Clutch (10 reviews), 4 - Glassdoor (1 review)

CEO: Tom Karwatka

So, let me repeat this once more: Continental, ING Bank, Tchibo, Intersport, Santander, Knauf, T-Mobile. Can you feel the envy?

With premium clients, monthly website traffic over 45k, and revenue growing a minimum of about 30% year on year, Divante is an inspiration.

It also got featured in Deloitte’s Fast 500 EMEA in 2017, with four-year revenue growth of 259%.

In our next blog post, we will look into reverse engineering Divante’s marketing and employer branding. We’ll dive into how traffic acquisition and conversion rate optimization are managed. If you want to learn more about how Divante managed to hack the enterprise sales process, you can watch Tom Karwatka speaking at the Web summit 2017:

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Tom Karwatka Presentation @ Web Summit 2017: hacking the enterprise sales process

Summing Up

Wrocław is a city which is becoming increasingly entrepreneurial. It started to evolve over time towards business based on specialized knowledge. The next step to be taken, based on PWC’s report, is an innovation-based economy.

Wrocław’s innovative potential is primarily the high-quality human capital as well as world class business representatives.

Wrocław’s specialization is primarily IT services, so there’s no surprise that companies like Monterail, Droids on Roids, Tooploox, and Divante have risen to Deloitte and Clutch tops.

Spoiler Alert!

Before going ahead with reading the rest of our Wroclaw software houses series, let me unfold some of my findings:

Don’t underestimate the power of open source. Take Divante for example, with its Open Loyalty and Vue Storefront it managed to impress Facebook and Whatsapp.

Long form content matters: case studies (Droids on Roids), research papers (Tooploox), reports (The State of Vue.js by Monterail), ebooks (Divante). Blog posts are merely for the awareness stage of the buyer’s journey, but you need to move the potential buyer down the funnel. And long-form content can do just that and establish you as a trustworthy and knowledgeable partner.

Choose your weapon, pick a niche. Tooploox goes with AI, Divante with e-commerce, Monterail established itself as the Vue.js guru.

Build your employer branding through social media channels and community involvement (Divante, Monterail, Tooploox, Droids on Roids)

Not enough talent pool? build it the goddamn pool: offer fellowships (like Tooploox), host workshops, hackathons (Divante), meetups or even hold your own conference (like Monterail’s Vue Conference)

Haven’t found a tech-skilled content writer, have your developers team involved in content writing! Monterail, the Droids on Roids, Tooploox and Divante are doing it.

Tools and marketing automation. Be it Hubspot (Monterail), Pipedrive (Tooploox), Hotjar(Tooploox) automation and marketing tools can save you time and money

Have a content marketing strategy: from content creation to promotion, be consistent and test a lot. Just check Monterail’s campaign on Vue.js, they’ve totally nailed it.

Now, let’s remember Wroclaw is not the only Polish city with potential for IT innovation. Poznan, Krakow, Warsaw are on the list too.

Because we don’t wanna fall in the “can't see the forest for the trees” trap, we made a macro analysis too, comparing the Polish, Ukrainian, and Romanian IT outsourcing markets in our Ultimate Guide To IT Outsourcing Companies in Central Eastern Europe.

There are a lot of stories worth reading in our IT outsourcing saga, so stay tuned.

if(window.strchfSettings === undefined) window.strchfSettings = {}; window.strchfSettings.stats = {url: "https://man-digital.storychief.io/wroclaw-software-house-5ca1ac2f94ad6?id=2056047666&type=12",title: "Wroclaw’s Software Houses Are Making a Statement in IT Outsourcing",id: "4f08255c-5e51-436c-99aa-71482a308009"}; (function(d, s, id) { var js, sjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) {window.strchf.update(); return;} js = d.createElement(s); js.id = id; js.src = "https://d37oebn0w9ir6a.cloudfront.net/scripts/v0/strchf.js"; js.async = true; sjs.parentNode.insertBefore(js, sjs); }(document, 'script', 'storychief-jssdk')) from Digital Marketing Automation Consulting | MAN Digital https://mandigitalblog.blogspot.com/2019/04/wroclaws-software-houses-are-making.html via https://mandigitalblog.blogspot.com/ Read more on our blog MAN Digital MAN Digital Blogger

#Digital Marketing Automation Consulting | MAN Digital

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nox-lathiaen · 7 years ago

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Data Warehouse Engineer

Job Title: Data Warehouse Engineer Location: San Luis Obispo, Irvine, San Diego, San Francisco, CA & Remote Also... Duration: Contract Client: Tech Mahindra Job Description: MINDBODY's Data Science department makes sense of our data world through meaningful and actionable insights, identifying trends, delivering reports, informing product and infrastructure advancements, and promoting a culture of data-driven decision making. The Data Engineering (DE) branch of MINDBODY's Data Science department is focused on providing innovative and large-scale data platform solutions in a shared services model to support enterprise data needs of MindBody. This involves building data pipelines to pull together information from different source systems; integrating, consolidating and cleansing data; and structuring it for use in reporting and analytical applications. This team also architects distributed systems, data stores, and collaborates with data science teams in building right solutions for them. The data provided by DE team is used by data science team in supporting key functions and initiatives within Product Development, Business Development, Customer Experience/Success, Marketing and Sales at MindBody. Data Engineer III focuses on designing, implementing and supporting new and existing data solutions- data processing, and data sets to support various advanced analytical needs. you will be designing, building and supporting data pipelines consuming data from multiple different source systems and transforming it into valuable and insightful information. You will have the opportunity to contribute to end-to-end platform design for our cloud architecture and work multi-functionally with operations, data science and the business segments to build batch and real-time data solutions. The role will be part of a team supporting our Corporate, Sales, Marketing, and Consumer business lines. MINIMUM QUALIFICATIONS AND REQUIREMENTS: 7+ years of relevant experience in one of the following areas: Data engineering, business intelligence or business analytics 5-7 years of supporting a large data platform and data pipelining 5+ years of experience in scripting languages like Python etc. 5+ years of experience with AWS services including S3, Redshift, EMR, 5+ years of experience with Big Data Technologies (Hadoop, Hive, HBase, Pig, Spark, etc.) Expertise in database design and architectural principles and methodologies Experienced in Physical data modeling Experienced in Logical data modeling Technical expertise should include data models, database design and data mining PRINCIPAL DUTIES AND RESPONSIBILITIES: Design, implement, and support a platform providing access to large datasets Create unified enterprise data models for analytics and reporting Design and build robust and scalable data integration (ETL) pipelines using SQL, Python, and Spark. As part of an Agile development team contribute to architecture, tools and development process improvements Work in close collaboration with product management, peer system, and software engineering teams to larify requirements and translate them into robust, scalable, operable solutions that work well within the overall data architecture Coordinate data models, data dictionaries, and other database documentation across multiple applications Leads design reviews of data deliverables such as models, data flows, and data quality assessments Promotes data modeling standardization, defines and drives adoption of the standards Work with Data Management to establish governance processes around metadata to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, and reusability of metadata Reference : Data Warehouse Engineer jobs Source: http://jobrealtime.com/jobs/technology/data-warehouse-engineer_i2861

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jbaquerot · 8 years ago

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Hewlett Packard Enterprise (HPE) announced new security capabilities at the RSA Conference in San Francisco this week to help protect big data and internet of things (IoT) workloads as well as a new tool to help investigate threats.

HPE developed its SecureData for Hadoop and IoT offering to help organizations protect sensitive information from being exposed in large data flows. At the core of the SecureData for Hadoop and IoT product is technology from the open-source Apache NiFi project. The NiFi code was originally built by the U.S. National Security Agency (NSA) to help solve the challenge of moving around large amounts of continuously streamed data efficiently and securely. "What we have built are interfaces that allow for the interception and protection of data in real time," Albert Biketi, vice president and general manager of HPE Security and Data Security at HPE, told eWEEK.

If, for example, the SecureData system sees a piece of data that is valuable, such as credit card information, flowing through a streaming data platform, that data can be anonymized and protected, according to Biketi. SecureData has a high capacity to protect structured and semi-structured data fields, he added.

#big data #iot #security

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jobsinchicago911 · 5 years ago

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Manager/Senior Cloud Platform Engineer

Where good people build rewarding careers.

Think that working in the insurance field can’t be exciting, rewarding and challenging? Think again. You’ll help us reinvent protection and retirement to improve customers’ lives. We’ll help you make an impact with our training and mentoring offerings. Here, you’ll have the opportunity to expand and apply your skills in ways you never thought possible. And you’ll have fun doing it. Join a company of individuals with hopes, plans and passions, all using and developing our talents for good, at work and in life.

Job Description

Allstate is looking for a Manager / Senior Cloud Platform Engineer within the ATSV Information Services Group (ISG), to lead the Cloud Analytics team. At ISG, we are responsible for the engineering and operation of the Allstate big data and real time analytics platforms. On the Cloud Analytics team, we are specialists helping ISG and Data Science (D3) teams support their big data and analytical efforts in the cloud, from planning stages to implementation. In this role you will work with AWS using Agile/Infrastructure as Code (IaC) methodologies to plan, test, and deploy cloud infrastructure using a variety of tools to support the enterprise analytics environment and be a coach / leader for the Cloud Analytics team.

Key Responsibilities

If you are an experienced hands-on engineer doing IaC in the cloud working on scalable, resilient, constantly evolving platforms, we’d like to talk to you. In this role you will:

Work with Big Data and Analytical teams to engineer and develop capabilities in the cloud that align with transformative growth business strategies and requirements.

Develop solutions for scale, resiliency and maintainability, which meet technical, security, and business needs for applications and workloads.

Assist other teams across ISG and Data Science (D3) with migration from on-premise to cloud workloads both from a conceptual and technology standpoint.

Test and deploy cloud-based services to support real-time analytics workloads.

Develop and support multi-step CI/CD deployment pipelines for cloud environment.

Help automate repeatable tasks to create efficiencies in our workflows and enable freedom for innovation.

Contribute to technology strategy, develop engineering roadmaps, and identify proof of concept use cases.

Champion good engineering practices and help teams to define and set up automated frameworks, focusing on delivering value.

Manage and develop staff including setting strategic direction, overseeing ongoing work, managing HR processes, coaching and mentoring.

Job Qualifications

Essential Qualifications

4+ years of relevant experience in infrastructure or platform development.

Experienced in utilizing “infrastructure as code” approach to provisioning.

Automation, Configuration Management (e.g. Ansible, Puppet), DevOps practices, CI/CD pipelines (e.g. Jenkins).

Familiarity with Python and Bash scripting.

Demonstrated knowledge of Amazon Web Services or similar cloud computing platform.

Experience managing or leading technical teams.

Hands-on style – willingness and competence in producing necessary changes in our infrastructure and processes.

Degree in Computer Science, MIS, or related area, or equivalent work experience.

Able to work effectively across organizational and geographical boundaries

Ability to clearly communicate ideas and solutions, representing the team across ISG and D3.

Continuous learner and a positive role model to staff.

Desirable Skills

Big Data Technologies such as Hadoop, EMR, Spark, Impala, Kafka, etc.

Good understanding of Linux – preferably RHEL and Ubuntu.

Storage – NAS, SAN, HDFS, Object Storage.

Basic networking skills – switching, routing, firewalls, load balancing.

Containers / Docker

The candidate(s) offered this position will be required to submit to a background investigation, which includes a drug screen.

Good Work. Good Life. Good Hands®.

As a Fortune 100 company and industry leader, we provide a competitive salary – but that’s just the beginning. Our Total Rewards package also offers benefits like tuition assistance, medical and dental insurance, as well as a robust pension and 401(k). Plus, you’ll have access to a wide variety of programs to help you balance your work and personal life — including a generous paid time off policy.

Learn more about life at Allstate. Connect with us on Twitter, Facebook, Instagram and LinkedIn or watch a video.

Allstate generally does not sponsor individuals for employment-based visas for this position.

Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.

For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance. For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.

To view the “EEO is the Law” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs

To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.

It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee’s terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.

from Jobs in Chicago https://ift.tt/3iZVsYh via IFTTT

#IFTTT #Jobs in Chicago

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latestmarketresearch · 5 years ago

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Covid-19 Impact on Big Data in the Insurance Market 2020

JULY 23, 2020: “Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

Amid the proliferation of real-time and historical data from sources such as connected devices, web, social media, sensors, log files and transactional applications, Big Data is rapidly gaining traction from a diverse range of vertical sectors. The insurance industry is no exception to this trend, where Big Data has found a host of applications ranging from targeted marketing and personalized products to usage-based insurance, efficient claims processing, proactive fraud detection and beyond.

To Request A Sample Copy Of This Report @: https://www.radiantinsights.com/research/big-data-in-the-insurance-industry-2018-2030/request-sample

SNS Telecom & IT estimates that Big Data investments in the insurance industry will account for more than $2.4 Billion in 2018 alone. Led by a plethora of business opportunities for insurers, reinsurers, insurance brokers, InsurTech specialists and other stakeholders, these investments are further expected to grow at a CAGR of approximately 14% over the next three years.

The “Big Data in the Insurance Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of Big Data in the insurance industry including key market drivers, challenges, investment potential, application areas, use cases, future roadmap, value chain, case studies, vendor profiles and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services investments from 2018 through to 2030. The forecasts are segmented for 8 horizontal submarkets, 8 application areas, 9 use cases, 6 regions and 35 countries.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

Topics Covered

The report covers the following topics:

- Big Data ecosystem

- Market drivers and barriers

- Enabling technologies, standardization and regulatory initiatives

- Big Data analytics and implementation models

- Business case, application areas and use cases in the insurance industry

- 20 case studies of Big Data investments by insurers, reinsurers, InsurTech specialists and other stakeholders in the insurance industry

- Future roadmap and value chain

- Profiles and strategies of over 270 leading and emerging Big Data ecosystem players

- Strategic recommendations for Big Data vendors and insurance industry stakeholders

- Market analysis and forecasts from 2018 till 2030

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:

Hardware, Software & Professional Services

- Hardware

- Software

- Professional Services

Horizontal Submarkets

- Storage & Compute Infrastructure

- Networking Infrastructure

- Hadoop & Infrastructure Software

- SQL

- NoSQL

- Analytic Platforms & Applications

- Cloud Platforms

- Professional Services

Application Areas

- Auto Insurance

- Property & Casualty Insurance

- Life Insurance

- Health Insurance

- Multi-Line Insurance

- Other Forms of Insurance

- Reinsurance

- Insurance Broking

Use Cases

- Personalized & Targeted Marketing

- Customer Service & Experience

- Product Innovation & Development

- Risk Awareness & Control

- Policy Administration, Pricing & Underwriting

- Claims Processing & Management

- Fraud Detection & Prevention

- Usage & Analytics-Based Insurance

- Other Use Cases

To Browse Full Research Report @: https://www.radiantinsights.com/research/big-data-in-the-insurance-industry-2018-2030

Regional Markets

- Asia Pacific

- Eastern Europe

- Latin & Central America

- Middle East & Africa

- North America

- Western Europe

Country Markets

- Argentina, Australia, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany, India, Indonesia, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, Norway, Pakistan, Philippines, Poland, Qatar, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Taiwan, Thailand, UAE, UK, USA

Key Questions Answered

The report provides answers to the following key questions:

- How big is the Big Data opportunity in the insurance industry?

- How is the market evolving by segment and region?

- What will the market size be in 2021, and at what rate will it grow?

- What trends, challenges and barriers are influencing its growth?

- Who are the key Big Data software, hardware and services vendors, and what are their strategies?

- How much are insurers, reinsurers, InsurTech specialists and other stakeholders investing in Big Data?

- What opportunities exist for Big Data analytics in the insurance industry?

- Which countries, application areas and use cases will see the highest percentage of Big Data investments in the insurance industry?

Key Findings

The report has the following key findings:

- In 2018, Big Data vendors will pocket more than $2.4 Billion from hardware, software and professional services revenues in the insurance industry. These investments are further expected to grow at a CAGR of approximately 14% over the next three years, eventually accounting for nearly $3.6 Billion by the end of 2021.

- Through the use of Big Data technologies, insurers and other stakeholders are beginning to exploit their data assets in a number of innovative ways ranging from targeted marketing and personalized products to usage-based insurance, efficient claims processing, proactive fraud detection and beyond.

- The growing adoption of Big Data technologies has brought about an array of benefits for insurers and other stakeholders. Based on feedback from insurers worldwide, these include but are not limited to an increase in access to insurance services by more than 30%, a reduction in policy administration workload by up to 50%, prediction of large loss claims with an accuracy of nearly 80%, cost savings in claims processing and management by 40-70%, accelerated processing of non-emergency insurance claims by a staggering 90%; and improvements in fraud detection rates by as much as 60%.

- In addition, Big Data technologies are playing a pivotal role in facilitating the adoption of on-demand insurance models - particularly in auto, life and health insurance, as well as the insurance of new and underinsured risks such as cyber crime.

List of Companies Mentioned

• 1010data

• Absolutdata

• Accenture

• Actian Corporation

• Adaptive Insights

• Adobe Systems

• Advizor Solutions

• Aegon

• AeroSpike

• Aetna

• AFS Technologies

• Alation

• Algorithmia

• Allianz Group

• Allstate Corporation

• Alluxio

• Alphabet

• ALTEN

• Alteryx

• AMD (Advanced Micro Devices)

• Anaconda

• Apixio

• Arcadia Data

• Arimo

• Arity

• ARM

• ASF (Apache Software Foundation)

• Atidot

• AtScale

• Attivio

• Attunity

• Automated Insights

• AVORA

• AWS (Amazon Web Services)

• AXA

• Axiomatics

• Ayasdi

• BackOffice Associates

• Basho Technologies

• BCG (Boston Consulting Group)

• Bedrock Data

• BetterWorks

• Big Panda

• BigML

• Birst

• Bitam

• Blue Medora

• BlueData Software

• BlueTalon

• BMC Software

• BOARD International

• Booz Allen Hamilton

• Boxever

• CACI International

• Cambridge Semantics

• Cape Analytics

• Capgemini

• Cazena

• Centrifuge Systems

• CenturyLink

• Chartio

• China Life Insurance Company

• Cigna

• Cisco Systems

• Civis Analytics

• ClearStory Data

• Cloudability

• Cloudera

• Cloudian

• Clustrix

• CognitiveScale

• Collibra

• Concirrus

• Concurrent Technology

• Confluent

• Contexti

• Couchbase

• Crate.io

Continued…………….

To See More Reports of This Category by Radiant Insights: https://latestmarkettrends.news.blog/

About Radiant Insights: Radiant Insights is a platform for companies looking to meet their market research and business intelligence requirements. It assist and facilitate organizations and individuals procure market research reports, helping them in the decision making process. The Organization has a comprehensive collection of reports, covering over 40 key industries and a host of micro markets. In addition to over extensive database of reports, experienced research coordinators also offer a host of ancillary services such as, research partnerships/ tie-ups and customized research solutions.

Media Contact:

Company Name: Radiant Insights, Inc

Contact Person: Michelle Thoras

Email:

[email protected]

Phone: (415) 349-0054

Address: 201 Spear St #1100, Suite #3036

City: San Francisco

State: California

Country: United States

#PR

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callmemoprah · 6 years ago

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What You Don’t Know About Data Management Platform Advertising Could Be Costing to More Than You Think

The 5-Minute Rule for Data Management Platform Advertising

The CDP produces a persistent consumer profile. If you decide on the great keyword phrases, high rankings are in fact a simple metric to attain. You don’t begin with the stage first.

There’s a preference you may use to determine if content sandboxing is allowed. In addition, there are more applications which are obvious. Segment 3 Visitors who only utilize mobile devices to observe the website and don’t stream music.

CDPs What is Ad Tech aren’t just databases. Wikis promote collaboration and reduce back version difficulties. Data alone, however, is not anything more than 1s and 0s.

The very best approach to strategy mobile would be to begin with clearly defined campaign objectives. The center of the challenge is because of how data quality does not have any intrinsic cost. In order to earn sense of storage you have to apply a multi-faceted strategy.

As we’ll see in the future, the response can play a crucial role in the way that you use your DMP when staying privacy-compliant. Here are a couple ways which you could use a wiki into your company. All you have to do would be to specify what sort of information you’re considering.

By taking advantage of a DMP that includes these choices provided for each and https://theappsolutions.com/ each tag in the collection phase of the procedure, you can refrain from getting stuck processing data you should not have or not having the capacity to track down info in case that you would like to delete it. The information in the DMP can help create insights and drive versions for attribution to assist you receive a much better comprehension of what is working and what’s less you participate in complicated advertising programs. For instance, a DLM merchandise would make it feasible for you to search stored information for a particular file type of a particular age, for instance, while an ILM product would allow you to search several sorts of saved files for instances of a particular bit of data, like a customer number.

Fixing first celebration information All entrepreneurs strive to enhance knowledge of their customers, and a lot of users and manufacturers are concerned concerning the condition of their very first party data. As a result, marketers are still often unable to use that intelligence to supply the message from the chance to the audience. I’ve seen many companies decide to do this manner.

The Fundamentals of Data Management Platform Advertising You Can Benefit From Starting Immediately

People today make purchase decisions based on an assortment of factors. Organizations who use cloud-based applications especially find it tough to keep up to maintain data orchestrated across systems. They may end up with the technology since they neglect to perform their due diligence.

Data https://mashable.com/2015/09/16/htc-vive-paint-virtual-reality/ research will become simpler and effective DMPs offer you an alternate to fragmented alternatives, which frequently concentrate on predetermined segments. Assignment help comes under the exact prices. Frequently the information analysis contains a particular degree of report creation.

Digital server deployments seem to be moving to mainstream IT manufacturing atmosphere. San Francisco established Periscope Data provides a data analysis tool which unifies business data across multiple unique data sources. IBM Db2 Hybrid Data Management provides you the chance to select which database or data warehouse works best for your organization.

The segments can subsequently be utilized for data evaluation. Imagine you’ve implemented a data-management solution provided by a favorite seller. A stage by definition ought to be extensible.

Understanding Data Management Platform Advertising

Digital marketing now is a mystery with several pieces, all which we are attempting to match together simultaneously. It’s priced on each a monthly or a yearly subscription fee, dependent on the selection of users that will need access to this program.

Another important matter to note is the ad sector is enormous. Let us look at a fantastic example.

Marketing agencies sit at the center between business advertising departments and possible customers. Nowadays, by definition, advertising also has the net and expands onto programs and cellular platforms. Most successful entrepreneurs strive to comprehend their customers so they can select the appropriate channels and the appropriate messages to achieve them.

Report audiences can get segment-specific vendor insights to recognize and assess key competitors determined by the in-depth assessment of capacities and success in the industry. They could use technologies such as web bugs to confirm if an impression is actually delivered. Any advertiser can produce their own affiliate program.

It is possible to use this data accumulated to construct audiences for particular advertising and marketing campaigns. Many research studies have shown that customers utilize a mean of 3-5 media resources to locate a neighborhood company, it’s no longer enough to put advertising in only one single medium. What is more, there are a lot of platforms available some more suited to particular requirements and study into various platforms is imperative to ensure make the a lot of the item.

In that circumstance, you don’t need to be concerned about anything and simply maintain a continuous flow of information. The whole period of the program phase is dependent mostly on the should acquire extra migration tools and the should develop extraction, loading, and superb checking program. To be able to earn sense of storage spending, you have to employ a multi-faceted strategy.

Our dissertation businesses include having the capacity to communicate with the writer during the period of the undertaking. You may also decide to continue to keep your Geofilter accessible for the very long duration and cover yearly. The end user does not have any method of knowing which is the right title.

These user insights permit the publisher to enhance the price of the inventory and will give a much better user experience. Profile management will help to make sure that the consumer’s individual preferences are put on the user’s virtual desktop and software, whatever the location and end point apparatus. Because of this, it makes it simpler to fit information to certain clients, even in instances of usage of anonymous ID.

The thing with Data Analysis is that you need to understand what are studying data for from the very first place for a means to make the most of it. The big quantities of data can be utilized in a lot of ways and the data can readily be engineered to fit various features of company operations. Over time, third-party data has received a rather terrible rap, largely because of the wide variety of privacy issues it raises.

The Meaning of Data Management Platform Advertising

The information format employed by Folio is very compatible with the plan of BIBFRAME2. Picking the most acceptable platform out of the audience can be hard, especially if you’re unsure exactly what the stage is about. Dealing with a large vendor can be difficult.

Success is dependent on Knowing what you would love to escape it. You’ll locate Spark included in the vast majority of Hadoop distributions now. Decide on the Pin you would like to market.

Aerospike This database provides a flash-optimized in-memory key-value shop. Asset lifecycle management is just another normal EAM computer software feature. Data collection also can help match data to identical specifics.

Data Management Platform Advertising Help!

The technical specifications for picture advertisements vary dependent on the ad goals, which usually means you need to inspect the specifics on Facebook Business. The price of Twitter advertisements is dependent on the ad type. Your mobile ads ought to be specifically intended for your tiny display, incorporating images that are simple to see on a pocket-sized device.

In tech, something similar applies. Or finding the revenue material you want the instant you want it. So unless you are selling one of the very niche goods on the business, there’s an extremely good chance your target audience has a presence on the website.

Apigee is a great example of a stage that comprises a developer portal. You will also know what are the advantages to using a DMP and the way you’re able to decide on the correct platform for your company needs.

Marketers get greater control over the promotion database and extra capacities. They can use technologies such as web bugs to verify if an impression is actually delivered. Some advertisers are spending money to market their goods in search outcome, just for Amazon to demonstrate a pop-up advertising for their very own private label merchandise.

It’s true that you have to do the heavy lifting of creating the base. The purpose of the project would be to generate a decentralized ecosystem, which can be utilized to build CPA solutions, which vary from affiliate programs to affiliate programs and associated products. Thus, to communicate with your audience most effectively, you need to uncover the complete potential of this data that you’ve already owned or have the capability to possess.

Regrettably, IT could be costly and out of this question for many tiny businesses. Many companies may feel that in case you use. Each company has a set of criteria which every employee is anticipated to follow.

The capacity planning tool can be employed by project supervisors to set up performance milestones and confirm performance targets are satisfied throughout deployment. It is possible that you set daily maximum and overall campaign budgets. The larger The requirement for keywords, the more complex the price per click.

The amount of information has grown too. All segments concerning data resources, deployment, end-user, and various areas are analysed with regard to basis points to comprehend the relative contributions of different segments to advertise development. Additional the information warehouses selected were unable to conduct machine learning.

The segments can subsequently be used for data evaluation. On the huge data front, vendors offer you advanced data management capabilities together with open source Hadoop distributions to handle and analyze huge volumes of information. A great platform makes it simple to tweak the information collection and information analysis based on your requirements.

The Data Management Platform Advertising Trap

It is critical that you’re assertive about what it is that you’re arguing, but it is unlikely that, at a dissertation project, you are going to have the capability to be definitive in closing an established academic discussion. There’s additionally a wiki page full of tools to support you get throughout the changes. Thus, the entire dissertation supplied is genuine and free from any sort of plagiarism.

If you are trying to find a solution for your business, it is a question you are asking. Naturally the value of each might ride on your own needs. All you need to do is to specify what type of information you’re contemplating.

These user insights permit the publisher to improve the purchase price of the inventory and can give a much better user experience. A thank you message inviting the shopper back not just establishes a relationship, but it also generates a terrific impression. Delivra includes a user interface which ensures the ideal messages reaches the appropriate individuals at just the proper moment.

The thing with Data Analysis is that you need to understand what exactly are studying data for from the very first place for a way to make the most of it. Basically, PII data comprises information which may be utilised to distinguish or trace somebody’s identity. Over time, third party data has received a rather terrible rap, largely because of the variety of privacy issues it raises.

People today make purchase decisions based on an range of factors. Many businesses may believe in the event that you use. They may end up with the technology because they neglect to do their due diligence.

Data research will get simpler and effective DMPs give you an alternate to fragmented alternatives, which often concentrate on predetermined sections. Assignment help comes under precisely the exact prices. Frequently the information analysis contains a particular degree of report creation.

What gear you ought to learn how to work at a job or place, will be determined by the systems employed. The medium could be new but the dimension of achievement is the exact same. Added the information warehouses selected were unable to conduct machine learning.

The segments can subsequently be utilized for data analysis. Adding a massive quantity of data for your own analysis, the platform may encounter connections you may have missed. A platform by definition ought to be extensible.

Data Management Platform Advertising – the Story

Must have an accurate Analysis to learn what the Market is prepared to pay. Data isn’t restricted to web pages only. A Universal ID is quite a mix of several IDs taken from several special devices and channels.

Being hair expert or a busy beauty it might be somewhat hard to manage your small small business venture. Additionally, there are several more uses that might be less obvious. Segment 3 Visitors who only utilize mobile devices to discover the website and don’t stream music.

CDPs aren’t just databases. Assumptions, actually, are extremely dangerous to create with internet advertising. Data alone, nevertheless, is not anything more than 1s and 0s.

Data Management Platform Advertising for Dummies

Each social networking provides different choices, and we are going to explore them in detail below. Marketing software collects plenty of information, but it will not allow you to know how to affect the people that you are targeting. It’s priced on every a monthly or an yearly subscription fee, determined by the selection of users who will need access to this program.

For instance, an automotive firm which uses DMP can produce a customized segment of clients that are thinking about purchasing new SUV. The absolute most ordinary DMP use instance is running a targeted campaign to a certain audience by way of a DSP.

This model is standard on social networks like Facebook and Twitter along with sites like Yelp. As customers use quite a few devices to interact with a brand, it is essential that each one of those interactions have been listed and assigned to the specific same customer profile. DMPs are significant elements of this data-driven advertising landscape and offer marketers with a potent tool for identifying and targeting high-value audiences.

The marketing revenue model isn’t new. A great deal of sales occur each day. No matter the cost, it’s likely an excellent deal for the two companies.

It is possible to utilize this data collected to construct audiences for particular advertising and advertising campaigns. Many research studies have demonstrated that customers utilize a mean of 3-5 media sources to locate a neighborhood business, it’s no longer sufficient to place advertising in only a single medium. What is more, there are a lot of platforms available more suited to certain requirements and research into various platforms is vital to ensure make the a lot of this item.

Source: http://mobimatic.io/2019/04/02/what-you-dont-know-about-data-management-platform-advertising-could-be-costing-to-more-than-you-think/

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shefsolutionllc · 7 months ago

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Shef Solutions LLC's Data Science Bootcamp in San Francisco: Accelerate Your Career

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thegloober · 7 years ago

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Pretty low level, pretty big deal: Apache Kafka and Confluent Open Source go mainstream

Featured stories

Apache Kafka, the open-source distributed messaging system, has steadily carved a foothold as the de facto real-time standard for brokering messages in scale-out environments. And if you think you have seen this opener before, it’s because you have.

Also: Pulsar graduates to being an Apache top-level project

Besides being fellow ZDNet’s Tony Baer opener for his piece commenting on Kafka usage survey in July, you’ve probably read something along these lines elsewhere, or had that feeling yourself. Yes, Kafka is in most whiteboards, but it’s mostly the whiteboards of early adopters, was the gist of Baer’s analysis.

With Kafka Summit kicking off today San Francisco, we took the opportunity for a chat with Jay Kreps, Kafka co-creator and Confluent CEO, on all things Kafka, as well as the broader landscape.

Going mainstream

Kreps indicated his belief that in the last year Kafka has actually gone mainstream. As evidence to back this claim, he cited use cases in four out of five biggest banks in the US, as well as the Bank of Canada: “These are 200 year-old organizations, and they don’t just jump at the first technology out of Silicon Valley. We are going mainstream in a big way,” Kreps asserted, while also mentioning big retail use cases.

While we have no reason to question these use cases, it’s hard to assess whether this translates to adoption in the majority of the market as well. Traditionally, big finance and retail are on the forefront of real-time use case adoption.

Also: We interrupt this revolution: Apache Spark changes the rules of the game

Still, it may take a while for this to spill over, so it depends on what one considers “mainstream.” Looking at Kafka Summit, however, we see a mix of Confluent staff and household names, which is the norm for events of this magnitude.

But what is driving this adoption? Something pretty low level, which is a pretty big deal, according to Kreps: The ability to integrate disparate systems via messaging, and to do this at scale and in real time. It’s not that this is a novel idea – messaging has been around for a while and it’s the key premise of Enterprise Service Bus (ESB) solutions for years.

Conceptually, Kafka is not all that different. The difference, Kreps said, is that older systems were not able to handle the scale that Kafka can: “We can scale to trillions of messages. New style, cloud data systems are just better at this, such techniques did not exist before. We benefited as we came around a bit later.”

Going cloud and real-time

The cloud is something Kreps emphasized, and the discussion around the latest developments in the field was centered around it. The recent Cloudera – Hortonworks merger, for example, touches upon this as well, according to Kreps.

“It was a smart move. These were two companies competing on the same product, which makes the competition more fierce, ironically. You’d think it’s people with different views that compete more fiercely, but it’s actually people with similar views. That really showed also in the business model,” Kreps said.

Also: Kafka: The story so far

Kreps believes that this competition slowed down progress in core Hadoop, as the need for differentiation resulted in more attention towards edge features. Case in point, he noted, the fact that HDFS, Hadoop’s file system, which historically has been a key component of its value proposition, is no longer the most economic way to store loads of data — cloud storage is now.

This could also be interpreted as a sign of moving away from batch processing that Hadoop started from and more toward real-time processing. Although Hadoop has been gradually grown to a full ecosystem, including streaming engines, the majority of its use cases are still batch-oriented, believes Kreps. How this will evolve, time will tell.

The cloud is gaining gravity in terms of data, and data-infrastructure platforms need to work both there and on premise. (Image: ktsimage, Getty Images/iStockphoto)

Despite Kreps pointing out the cloud as a gravitational point, and Hadoop actually moving toward it in the last couple of years, Confluent is not going to pursue a cloud-only policy. As opposed to data science workloads, which can be hosted either on premise or in the cloud, the kind of data infrastructure that Kafka provided must work on both, argued Kreps.

Since many organizations still have huge investments in software and infrastructure built over years in their data centers, any move to the cloud will be gradual. Confluent’s hosted version of Kafka plus proprietary extensions will continue to work seamlessly with on-premise Kafka or Confluent open source, said Kreps. He also emphasized Kafka support for Kubernetes, noting that any stateful data system has to put in some effort to make this work.

Streaming coopetition and real-time machine learning

In terms of differentiation with other streaming platforms, Kreps pointed out that these are mostly geared toward analytics, while Kafka is infrastructure on which operational systems can be, and are, built. When wondering whether Kafka could also be moving in the analytics direction, Kreps did not give any such indication, and questioned the applicability of real-time machine learning (ML):

Also: An inside look at Apache Kafka adoption TechRepublic

“What is the use of a real-time machine learning platform? When i was in school, ironically the focus of my advisors was real-time ML — ironically, because ML was not very popular back then, let alone real-time ML.

We were struggling to name a mainstream production system using real-time ML. And the idea of having a ML algorithm retrain itself in real-time is not necessarily positive. Most of the time, the effort is to have enough checks and balances in places to make sure ML really works even when working with batch data.

And if you look at ML algorithms built by people who build databases and infrastructure, they are never as good, which is normal. There is a separate ecosystem for data science, and the best stuff is separate from the big infrastructure projects.

The reality is that Spark machine learning is mostly used for offline ML. Streaming brings together all the data needed for this, and Kafka works with other streaming platforms, too.”

Kafka is a key element of the streaming landscape, but it also works complementary to other streaming platforms.

More often than not, Kafka seems to be mentioned in the same breath, or whiteboard, with a number of other systems, including streaming ones. Although some might say this means it will be hard for Kafka to come into its own, its position in those architectures also means it’s equally hard to take it out of the equation.

Although no big announcement is reserved for this Kafka Summit, Kafka and Confluent have had a few of those in the last year — KSQL and version 5.0 being the most prominent ones — and seems to be well on the way to the mainstream.

Previous and related coverage:

Confluent release adds enterprise, developer, IoT savvy to Apache Kafka

Confluent, the company founded by the creators of streaming data platform Apache Kafka, is announcing a new release today. Confluent Platform 5.0, based on yesterday’s release of open source Kafka 2.0, adds enterprise security, new disaster recovery capabilities, lots of developer features, and important IoT support.

Hortonworks ups its Kafka Game

Ahead of the Strata conference next month, Hortonworks is focusing on streaming data as it introduces a new Kafka management tool and adds some refinements to its DataFlow product.

Kafka is establishing its toehold

Data pipelines were the headline from the third annual survey of Apache Kafka use. Behind anecdotal evidence of a growing user base, Kafka is still at the early adopter stage and skills remain hard to find.

Confluent brings fully-managed Kafka to the Google Cloud Platform

The partnership between Confluent and Google extends the Kafka ecosystem, making it easier to consume with Google Cloud services for machine learning, analytics and more.

Source: https://bloghyped.com/pretty-low-level-pretty-big-deal-apache-kafka-and-confluent-open-source-go-mainstream/

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jobsaggregationco · 7 years ago

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Data Warehouse Engineer

Job Title: Data Warehouse Engineer Location: San Luis Obispo, Irvine, San Diego, San Francisco, CA & Remote Also... Duration: Contract Client: Tech Mahindra Job Description: MINDBODY's Data Science department makes sense of our data world through meaningful and actionable insights, identifying trends, delivering reports, informing product and infrastructure advancements, and promoting a culture of data-driven decision making. The Data Engineering (DE) branch of MINDBODY's Data Science department is focused on providing innovative and large-scale data platform solutions in a shared services model to support enterprise data needs of MindBody. This involves building data pipelines to pull together information from different source systems; integrating, consolidating and cleansing data; and structuring it for use in reporting and analytical applications. This team also architects distributed systems, data stores, and collaborates with data science teams in building right solutions for them. The data provided by DE team is used by data science team in supporting key functions and initiatives within Product Development, Business Development, Customer Experience/Success, Marketing and Sales at MindBody. Data Engineer III focuses on designing, implementing and supporting new and existing data solutions- data processing, and data sets to support various advanced analytical needs. you will be designing, building and supporting data pipelines consuming data from multiple different source systems and transforming it into valuable and insightful information. You will have the opportunity to contribute to end-to-end platform design for our cloud architecture and work multi-functionally with operations, data science and the business segments to build batch and real-time data solutions. The role will be part of a team supporting our Corporate, Sales, Marketing, and Consumer business lines. MINIMUM QUALIFICATIONS AND REQUIREMENTS: 7+ years of relevant experience in one of the following areas: Data engineering, business intelligence or business analytics 5-7 years of supporting a large data platform and data pipelining 5+ years of experience in scripting languages like Python etc. 5+ years of experience with AWS services including S3, Redshift, EMR, 5+ years of experience with Big Data Technologies (Hadoop, Hive, HBase, Pig, Spark, etc.) Expertise in database design and architectural principles and methodologies Experienced in Physical data modeling Experienced in Logical data modeling Technical expertise should include data models, database design and data mining PRINCIPAL DUTIES AND RESPONSIBILITIES: Design, implement, and support a platform providing access to large datasets Create unified enterprise data models for analytics and reporting Design and build robust and scalable data integration (ETL) pipelines using SQL, Python, and Spark. As part of an Agile development team contribute to architecture, tools and development process improvements Work in close collaboration with product management, peer system, and software engineering teams to larify requirements and translate them into robust, scalable, operable solutions that work well within the overall data architecture Coordinate data models, data dictionaries, and other database documentation across multiple applications Leads design reviews of data deliverables such as models, data flows, and data quality assessments Promotes data modeling standardization, defines and drives adoption of the standards Work with Data Management to establish governance processes around metadata to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, and reusability of metadata Reference : Data Warehouse Engineer jobs source http://jobsaggregation.com/jobs/technology/data-warehouse-engineer_i2861