#data ingestion

[jcmarchi]

Unlock the other 99% of your data - now ready for AI

New Post has been published on https://thedigitalinsider.com/unlock-the-other-99-of-your-data-now-ready-for-ai/

Unlock the other 99% of your data - now ready for AI

For decades, companies of all sizes have recognized that the data available to them holds significant value, for improving user and customer experiences and for developing strategic plans based on empirical evidence.

As AI becomes increasingly accessible and practical for real-world business applications, the potential value of available data has grown exponentially. Successfully adopting AI requires significant effort in data collection, curation, and preprocessing. Moreover, important aspects such as data governance, privacy, anonymization, regulatory compliance, and security must be addressed carefully from the outset.

In a conversation with Henrique Lemes, Americas Data Platform Leader at IBM, we explored the challenges enterprises face in implementing practical AI in a range of use cases. We began by examining the nature of data itself, its various types, and its role in enabling effective AI-powered applications.

Henrique highlighted that referring to all enterprise information simply as ‘data’ understates its complexity. The modern enterprise navigates a fragmented landscape of diverse data types and inconsistent quality, particularly between structured and unstructured sources.

In simple terms, structured data refers to information that is organized in a standardized and easily searchable format, one that enables efficient processing and analysis by software systems.

Unstructured data is information that does not follow a predefined format nor organizational model, making it more complex to process and analyze. Unlike structured data, it includes diverse formats like emails, social media posts, videos, images, documents, and audio files. While it lacks the clear organization of structured data, unstructured data holds valuable insights that, when effectively managed through advanced analytics and AI, can drive innovation and inform strategic business decisions.

Henrique stated, “Currently, less than 1% of enterprise data is utilized by generative AI, and over 90% of that data is unstructured, which directly affects trust and quality”.

The element of trust in terms of data is an important one. Decision-makers in an organization need firm belief (trust) that the information at their fingertips is complete, reliable, and properly obtained. But there is evidence that states less than half of data available to businesses is used for AI, with unstructured data often going ignored or sidelined due to the complexity of processing it and examining it for compliance – especially at scale.

To open the way to better decisions that are based on a fuller set of empirical data, the trickle of easily consumed information needs to be turned into a firehose. Automated ingestion is the answer in this respect, Henrique said, but the governance rules and data policies still must be applied – to unstructured and structured data alike.

Henrique set out the three processes that let enterprises leverage the inherent value of their data. “Firstly, ingestion at scale. It’s important to automate this process. Second, curation and data governance. And the third [is when] you make this available for generative AI. We achieve over 40% of ROI over any conventional RAG use-case.”

IBM provides a unified strategy, rooted in a deep understanding of the enterprise’s AI journey, combined with advanced software solutions and domain expertise. This enables organizations to efficiently and securely transform both structured and unstructured data into AI-ready assets, all within the boundaries of existing governance and compliance frameworks.

“We bring together the people, processes, and tools. It’s not inherently simple, but we simplify it by aligning all the essential resources,” he said.

As businesses scale and transform, the diversity and volume of their data increase. To keep up, AI data ingestion process must be both scalable and flexible.

“[Companies] encounter difficulties when scaling because their AI solutions were initially built for specific tasks. When they attempt to broaden their scope, they often aren’t ready, the data pipelines grow more complex, and managing unstructured data becomes essential. This drives an increased demand for effective data governance,” he said.

IBM’s approach is to thoroughly understand each client’s AI journey, creating a clear roadmap to achieve ROI through effective AI implementation. “We prioritize data accuracy, whether structured or unstructured, along with data ingestion, lineage, governance, compliance with industry-specific regulations, and the necessary observability. These capabilities enable our clients to scale across multiple use cases and fully capitalize on the value of their data,” Henrique said.

Like anything worthwhile in technology implementation, it takes time to put the right processes in place, gravitate to the right tools, and have the necessary vision of how any data solution might need to evolve.

IBM offers enterprises a range of options and tooling to enable AI workloads in even the most regulated industries, at any scale. With international banks, finance houses, and global multinationals among its client roster, there are few substitutes for Big Blue in this context.

To find out more about enabling data pipelines for AI that drive business and offer fast, significant ROI, head over to this page.

[rajaniesh]

Unlock Powerful Data Strategies: Master Managed and External Tables in Fabric Delta Lake

Are you ready to unlock powerful data strategies and take your data management skills to the next level? In our latest blog post, we dive deep into mastering managed and external tables in Delta Lake within Microsoft Fabric.

Welcome to our series on optimizing data ingestion with Spark in Microsoft Fabric. In our first post, we covered the capabilities of Microsoft Fabric and its integration with Delta Lake. In this second installment, we dive into mastering Managed and External tables. Choosing between managed and external tables is a crucial decision when working with Delta Lake in Microsoft Fabric. Each option…

[techinfotrends]

Data ingestion is core to any data refinement procedure that targets revealing hidden data insights. Right from collecting data to bringing it to the insightful revelation stage is a work of art. This is what data ingestion deals with.

Making it indispensable to your business processes shall yield greater results in the long-term future. Facilitating enhanced data analytics quality, trusted data-driven decision-making, and leveraging flexibility are all the perks that your organization can gain. Therefore, understanding the different types of data ingestion, and how they perform in real-time is a hard nut to crack.

Making it easier for you, there are popular and globally trusted data science certifications that can enhance your comprehension of these key concepts. These are streamed to prepare you for the organizational big data handling ahead.

There is a massive demand for skilled and certified data science professionals with the requisite knowledge of data ingestion tools worldwide. In the years as we advance through 2026, there will be 11.5 million jobs created for certified data scientists (The US Bureau of Labor Statistics). Make yourself a quick pick in the global career field that commands high respect for skills, and expertise, and offers a whopper of a salary internationally.

Building a thriving career progression with these skills and credentials gracing your portfolio for your dream data science job role with your preferred industry giant. Master data ingestion with USDSI® Data Science certifications today!

[navybluetriangles]

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[tweedfrog]

Need to know if every single era had those incredibly annoying contrarians who, when you point out a fairly obvious recent issue start "not everything is because of 1 thing"-ing you.

Like idk bro if you were previously a healthy 20 year old and after a week long viral infection you can't stand without getting palpations yes statistically it's likely it was covid and now you've got long covid.

If you live on a mountain outside of the tropics and got hit with a fucking hurricane out of nowhere it's likely climate change and not some random freak event that would have happened if we were all using solar panels.

It's just exhausting to deal with. If i was in the middle of the eruption of Mt Vesuvius and someone was like "um akshually this isn't strange at all and can be explained by something else" i think I'd have shoved them into the lava myself.

[alatariel-galadriel]

google’s generative ai search results have started showing up in Firefox and I hate it I hate it I hate it i hate it I hate it I HATE IT

[boonars]

Day 4: Ingest and Transform Data in Microsoft Fabric – No-Code and Pro-Code Guide

Ingest and Transform Data in Microsoft Fabric | No-Code and Pro-Code (Day 4) Published: July 5, 2025 🚀 Introduction Now that you’ve created your first Microsoft Fabric workspace, it’s time to bring in some data! In this article, you’ll learn how to ingest data into your Lakehouse or Warehouse and transform it using both no-code (Dataflows Gen2) and pro-code (Notebooks) methods. Whether you’re a…

[vague-humanoid]

At the California Institute of the Arts, it all started with a videoconference between the registrar’s office and a nonprofit.

One of the nonprofit’s representatives had enabled an AI note-taking tool from Read AI. At the end of the meeting, it emailed a summary to all attendees, said Allan Chen, the institute’s chief technology officer. They could have a copy of the notes, if they wanted — they just needed to create their own account.

Next thing Chen knew, Read AI’s bot had popped up inabout a dozen of his meetings over a one-week span. It was in one-on-one check-ins. Project meetings. “Everything.”

The spread “was very aggressive,” recalled Chen, who also serves as vice president for institute technology. And it “took us by surprise.”

The scenariounderscores a growing challenge for colleges: Tech adoption and experimentation among students, faculty, and staff — especially as it pertains to AI — are outpacing institutions’ governance of these technologies and may even violate their data-privacy and security policies.

That has been the case with note-taking tools from companies including Read AI, Otter.ai, and Fireflies.ai.They can integrate with platforms like Zoom, Google Meet, and Microsoft Teamsto provide live transcriptions, meeting summaries, audio and video recordings, and other services.

Higher-ed interest in these products isn’t surprising.For those bogged down with virtual rendezvouses, a tool that can ingest long, winding conversations and spit outkey takeaways and action items is alluring. These services can also aid people with disabilities, including those who are deaf.

But the tools can quickly propagate unchecked across a university. They can auto-join any virtual meetings on a user’s calendar — even if that person is not in attendance. And that’s a concern, administrators say, if it means third-party productsthat an institution hasn’t reviewedmay be capturing and analyzing personal information, proprietary material, or confidential communications.

“What keeps me up at night is the ability for individual users to do things that are very powerful, but they don’t realize what they’re doing,” Chen said. “You may not realize you’re opening a can of worms.“

The Chronicle documented both individual and universitywide instances of this trend. At Tidewater Community College, in Virginia, Heather Brown, an instructional designer, unwittingly gave Otter.ai’s tool access to her calendar, and it joined a Faculty Senate meeting she didn’t end up attending. “One of our [associate vice presidents] reached out to inform me,” she wrote in a message. “I was mortified!”

[pythonjobsupport]

Data Ingestion Security Patterns - Tips and Tricks

Ready to Learn Synapse in 5 Minutes? This month’s video is on data ingestion security patterns tips and tricks. Ryan continues … source

[juliebowie]

Real-Time Data Ingestion: Strategies, Benefits, and Use Cases

Summary: Master real-time data! This guide explores key concepts & strategies for ingesting & processing data streams. Uncover the benefits like improved decision-making & fraud detection. Learn best practices & discover use cases across industries.

Introduction

In today's data-driven world, the ability to analyse information as it's generated is becoming increasingly crucial. Traditional batch processing, where data is collected and analysed periodically, can leave businesses lagging behind. This is where real-time data ingestion comes into play.

Overview Real-Time Data Ingestion

Real-time data ingestion refers to the continuous process of capturing, processing, and storing data streams as they are generated. This data can come from various sources, including sensor networks, social media feeds, financial transactions, website traffic logs, and more.

By ingesting and analysing data in real-time, businesses can gain valuable insights and make informed decisions with minimal latency.

Key Concepts in Real-Time Data Ingestion

Data Streams: Continuous flows of data generated by various sources, requiring constant ingestion and processing.

Event Stream Processing (ESP): Real-time processing engines that analyse data streams as they arrive, identifying patterns and extracting insights.

Microservices Architecture: Breaking down data processing tasks into smaller, independent services for increased scalability and agility in real-time environments.

Data Pipelines: Defined pathways for data to flow from source to destination, ensuring seamless data ingestion and transformation.

Latency: The time it takes for data to travel from its source to the point of analysis. Minimising latency is crucial for real-time applications.

Strategies for Implementing Real-Time Data Ingestion

Ready to harness the power of real-time data? Dive into this section to explore key strategies for implementing real-time data ingestion. Discover how to choose the right tools, ensure data quality, and design a scalable architecture for seamless data capture and processing.

Choosing the Right Tools: Select data ingestion tools that can handle high-volume data streams and offer low latency processing, such as Apache Kafka, Apache Flink, or Amazon Kinesis.

Data Stream Preprocessing: Clean, filter, and transform data streams as they are ingested to ensure data quality and efficient processing.

Scalability and Performance: Design your real-time data ingestion architecture to handle fluctuating data volumes and maintain acceptable processing speed.

Monitoring and Alerting: Continuously monitor your data pipelines for errors or performance issues. Implement automated alerts to ensure timely intervention if problems arise.

Benefits of Real-Time Data Ingestion

Explore the transformative benefits of real-time data ingestion. Discover how it empowers businesses to make faster decisions, enhance customer experiences, and optimise operations for a competitive edge.

Enhanced Decision-Making: Real-time insights allow businesses to react quickly to market changes, customer behaviour, or operational issues.

Improved Customer Experience: By analysing customer interactions in real-time, businesses can personalise recommendations, address concerns promptly, and optimise customer journeys.

Fraud Detection and Prevention: Real-time analytics can identify suspicious activity and prevent fraudulent transactions as they occur.

Operational Efficiency: Monitor machine performance, resource utilisation, and potential equipment failures in real-time to optimise operations and minimise downtime.

Risk Management: Real-time data analysis can help predict and mitigate potential risks based on real-time market fluctuations or social media sentiment.

Challenges in Real-Time Data Ingestion

Real-time data streams are powerful, but not without hurdles. Dive into this section to explore the challenges of high data volume, ensuring data quality, managing complexity, and keeping your data secure.

Data Volume and Velocity: Managing high-volume data streams and processing them with minimal latency can be a challenge.

Data Quality: Maintaining data quality during real-time ingestion is crucial, as errors can lead to inaccurate insights and poor decision-making.

Complexity: Real-time data pipelines involve various technologies and require careful design and orchestration to ensure smooth operation.

Security Concerns: Protecting sensitive data while ingesting and processing data streams in real-time requires robust security measures.

Use Cases of Real-Time Data Ingestion

Learn how real-time data ingestion fuels innovation across industries, from fraud detection in finance to personalised marketing in e-commerce. Discover the exciting possibilities that real-time insights unlock.

Fraud Detection: Financial institutions use real-time analytics to identify and prevent fraudulent transactions as they occur.

Personalized Marketing: E-commerce platforms leverage real-time customer behaviour data to personalise product recommendations and promotions.

IoT and Sensor Data Analysis: Real-time data from sensors in connected devices allows for monitoring equipment health, optimising energy consumption, and predicting potential failures.

Stock Market Analysis: Financial analysts use real-time data feeds to analyse market trends and make informed investment decisions.

Social Media Monitoring: Brands can track social media sentiment and brand mentions in real-time to address customer concerns and manage brand reputation.

Best Practices for Real-Time Data Ingestion

Unleashing the full potential of real-time data! Dive into this section for best practices to optimise your data ingestion pipelines, ensuring quality, performance, and continuous improvement.

Plan and Design Thoroughly: Clearly define requirements and design your real-time data ingestion architecture considering scalability, performance, and security.

Choose the Right Technology Stack: Select tools and technologies that can handle the volume, velocity, and variety of data you expect to ingest.

Focus on Data Quality: Implement data cleaning and validation techniques to ensure the accuracy and consistency of your real-time data streams.

Monitor and Maintain: Continuously monitor your data pipelines for errors and performance issues. Implement proactive maintenance procedures to ensure optimal performance.

Embrace Continuous Improvement: The field of real-time data ingestion is constantly evolving. Stay updated on new technologies and best practices to continuously improve your data ingestion pipelines.

Conclusion

Real-time data ingestion empowers businesses to operate in an ever-changing environment. By understanding the key concepts, implementing effective strategies, and overcoming the challenges, businesses can unlock the power of real-time insights to gain a competitive edge.

From enhanced decision-making to improved customer experiences and operational efficiency, real-time data ingestion holds immense potential for organisations across diverse industries. As technology continues to advance, real-time data ingestion will become an even more critical tool for success in the data-driven future.

Frequently Asked Questions

What is the Difference Between Real-Time and Batch Data Processing?

Real-time data ingestion processes data as it's generated, offering near-instant insights. Batch processing collects data periodically and analyses it later, leading to potential delays in decision-making.

What are Some of The Biggest Challenges in Real-Time Data Ingestion?

High data volume and velocity, maintaining data quality during processing, and ensuring the security of sensitive data streams are some of the key challenges to overcome.

How Can My Business Benefit from Real-Time Data Ingestion?

Real-time insights can revolutionise decision-making, personalise customer experiences, detect fraud instantly, optimise operational efficiency, and identify potential risks before they escalate.

[rajaniesh]

Unveiling the Power of Delta Lake in Microsoft Fabric

Discover how Microsoft Fabric and Delta Lake can revolutionize your data management and analytics. Learn to optimize data ingestion with Spark and unlock the full potential of your data for smarter decision-making.

In today’s digital era, data is the new gold. Companies are constantly searching for ways to efficiently manage and analyze vast amounts of information to drive decision-making and innovation. However, with the growing volume and variety of data, traditional data processing methods often fall short. This is where Microsoft Fabric, Apache Spark and Delta Lake come into play. These powerful…

[charseraph]

C&A is a neobotanics and nooscionics lab. In other words, they grow and train sophont AIs, “seedlets,” and design software and hardware to interface organic minds with digital systems.

It’s a small enough company to draw little suspicion, but credible enough to be contracted by big name operations (mainly military).

They accidentally trapped a person in a noospace, the “noosciocircus,” with Caine, a seedlet grown and owned by C&A. He’s a well meaning seedlet, tasked to keep the trapped person sane as C&A keeps their body alive as long as possible.

In an effort to recover the person from the inside, they sent in another only to trap them as well. Their cumulating mistake becomes harder to pull the plug on as it would kill both the trapped and Caine, an expensive investment who just also happens to be relaying immensely valuable nootic data from his ongoing simulation.

C&A continues to send agents to assist the trapped from within, each with relevant skills. They’re getting a bit desperate, since the pool of candidates is limited to those who work with C&A and would not draw too much attention if gone missing.

So, the noosciocircus becomes testing ground for lesser semiohazards.

Semiohazards are stimuli that trigger a destructive response in the minds of perceivers. Semiohazards can be encoded into any medium, but are generally easiest to encode into sights and air pressure sequences. The effect, “a mulekick,” can range in severity from temporarily disabled breathing, to seizure, to brain death.

Extreme amputations (“truncations”) occur when a trapped agent ingests a semiohazard that shuts off the brain’s recognition of some body part as its own. Sieving is a last resort to permanently mechanically support the life of the trapped. Thanks to modern advancements, this is cheap and sustainable. Those overexposed to the hazards become the abstracted and are considered lost. Their bodies are kept alive for archival.

Semiohazards being a current hotspot of discovery and design means C&A is sending in semiotic specialists alongside programmers. Ragatha was sent in to provide the trapped with nootic endurance training, but she underestimated the condition of the trapped. Gangle, too, was sent to help the trapped navigate their new nootic state, but her own dealt avatar clotheslined her progress. She wasn’t too stable entering to begin with, but C&A’s options are limited.

[bunnis-monsters]

How would we "give birth" to bee hybrids?

Bc obviously theres egg, but do we lay them like bees do in the honeycomb?

Or do we give birth like a person would?

This is actually highly debated amongst different hives.

Some believe laying eggs in a honeycomb is both the most natural and best way to go about birthing. It’s what bees did and their ancestors did, so that’s what they should do!

There are others that say incubating them in your womb and giving birth to them live creates more loyal subjects that will stick to their queen through anything!

The truth? Either way is fine and gets the job done. There’s very little information to back up which way is better for the baby bees, as giving birth to live babies is new and hasn’t had a higher mortality rate than laying eggs into a comb.

Scientist bees are still collecting data from different hives to see which way is truly the best method… but I’d say it depends on the mother and what she thinks is best for her own body.

Just like some mothers think ingesting honey straight from the father’s own collection will help build their immunity, others think introducing the little ones to a wide array of honeys at an early age can make sure they’re healthy and will make better honey later in life. It’s a simple difference of opinion that makes no real difference either way.

A baby that survives incubation is a good baby, whether it’s from birthing or being laid by their mother.

Good job mamas, you’re doing your best!

a/n: tried to make this read like an article from a mommy blog that tries to stay neutral on topics lol

[smallestapplin]

What if the Cybertronians saw the reader drinking blue gatorade and thought it was Energon.

I went with Prowl headcanons, he doesnt get enough love.

-

-

- Energon is known, at least to the autobots on Earth, to be toxic to human, Ratchet stressed after an accident that no human companion of theirs should be exposed to it for too long and to never ingest it for it could at minium do serious harm, but more likely kill their little human.

- Prowl does not mind you always bothering him as he works, he’s grown use to you and your antics making it easier to block you out or at least still get things done. So when you walk into his office, greeting him as always, he doesn’t look away from his data pad as he greets you in return.

- You climb up his desk (with the stairs he absolutely did not build in so you could climb up it safer) and sit near his servos.

- You chat with him with ease, asking about his day which he tells you little about, but he’s still nice to be with.

- Bright blue catches his attention off the corner of his optics, he almost assumed you brought him the worlds smallest Energon cube, until he turns his head and sees you drinking it. His optics widen a fraction and before you know it you’re being yanked into the air, you bottle falling from your hands spilling the liquid all over his desk, but he doesn’t care.

- You ask him what’s wrong but he doesn’t even answer you as he’s speeding out of his office, swiftly transforming making your head spin as you find yourself in the passenger seat. His sirens blaring as he drives, speeding down the hall making any autobot jump to the side to get out of his way.

- “Prowl, what’s going on!?”

- “You are a fragging idiot! We can make it to Ratchet, I won’t let you offline.”

- You’re so confused. Prowl slams on his brakes as he bursts through the medbay doors, gaining the attention of a newly pissed off Racteht, before transforming once more, this time holding you out to the medbot.

- “They drank energon!”

- And like that Ratchet is taking you, setting you on the medical berth and hooking so many things up to you as he’s loudly scolding you for even touching energon. But you can’t remember drinking energon, you didn’t have any! The only time you’re even near it is when you’re around them as they drink it.

- Prowl and Ratchet talk amongst themselves, though it’s clear they are both worried. Ratchet is not trained to handle humans, your bodies are so much more fragile and complex than he studied for. It takes Prowl telling Ratchet the story for it to finally click in your head.

“That wasn’t energon, that was a Gatorade!”

The two bots look at you, optics narrowed, squinting at you in suspicion.

“Aren’t gators those lizard things you spoke of with the powerful bite force? Why would they need aid?” Prowl questions, crossing his arms over his chassis.

“And why would you be drinking it?” Ratchet follows up.

You have to pull up your phone to look it up in bigger words to get it through their processors that you really are fine, it was just a tasty drink! Though it doesn’t help the two bots groans, shaking their helms and muttering something humans being weird, and making odd scrap as always.

But as Prowl holds you in his servo as you two leave the medbay, he looks at you with a stern expression.

“Don’t you ever do that to me again, understood?”

You have to fight back a smile, knowing how worried he must’ve been, “I promise Prowl, I’ll make sure to let you know what I got before hand.”

He’s a worry wot, give him a break.