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- 💾 Top 12 Data and AI Trends for 2024
💾 Top 12 Data and AI Trends for 2024
The Key Data and AI Trends to Watch in 2024
Top 12 Data and AI Trends for 2024
The world of data and AI is always changing, and it's important to keep up.
2023 was a big year for Generative AI (GenAI), and 2024 is looking to be more of the same. But there's a twist. Instead of just talking about AI, teams are going to use it to solve real business problems. It's like moving from just chatting about AI to actually putting it to work.
As GenAI keeps growing, it's going to lift the whole data industry to new heights. This means better ways of doing things are coming.
So, what's next for teams working with data and AI? Here are my top 10 predictions for where things are heading and how your team can stay ahead of the game.
1. Data Teams Will Work Like App-Making Teams
Think of how teams make apps and software. Now, that's how data teams are starting to work too. They're treating data not just as numbers but like real products you can use.
These teams are getting more organized. They're planning their work in sprints (short, focused work periods), making clear documents, and setting service standards, just like teams who make apps.
As data gets more important, these teams are becoming key players in companies. They're being managed just as seriously as the teams that make the main products or software. So, expect to see data teams step up their game, working in smart, structured ways just like the best app developers do.
2. App-Making Teams Will Also Become Data Experts
Imagine building a house without thinking about the bricks you need. That's like making apps or AI without focusing on the data. It just doesn't work out well.
In the tech world, making apps and understanding data are becoming the same thing. You can't do one without the other. AI is a big deal now, and it needs good data to be smart and useful.
So, engineers who create apps and AI need to be good with data too. They have to understand it, know how to use it, and make sure it makes their AI better and more valuable. In short, being good at making apps now means being good at handling data too.
3. LLMs Are Changing Technology A Lot
Large Language Models (LLMs) are super-smart tools that understand and use words like humans. They’ve really changed how we use technology in the past year. Now, everyone, from big companies to small teams, wants to use this kind of smart AI (called GenAI) for different things.
These LLMs aren’t stopping anytime soon. They’re going to keep changing things in 2024 and after. They make people want more data and need new tech setups, like vector databases (think of these as special shelves to store and use data for AI).
With LLMs, automatically analyzing data and using it in products is becoming normal. The big question for 2024 is: How do we make sure these new tools are really helpful and not just something flashy to talk about?
4. RAG Will Be Super Popular
RAG, short for Retrieval-Augmented Generation, is becoming a big deal in AI. It's like a new tool that makes AI smarter by using good, well-organized data.
After some big mistakes with AI, it's clear now that AI needs the right kind of data to work well. That’s where RAG comes in. It lets teams add their own special data to AI, making it more useful for their specific needs.
This RAG method is pretty new (it started in 2020), and teams are still figuring out the best ways to use it. But it's catching on fast. It’s helping companies make their AI products better and really show value to the people using them.
5. XOps: Making Businesses Smarter
XOps is all about making businesses work better with AI and data analysis. It started with something called DevOps, which mixes up development (making stuff) and operations (keeping things running smoothly). The big idea is to make businesses work better and give customers a great experience using DevOps' smart ways.
XOps focuses on being reliable, reusing stuff instead of always making new things, and doing things in a way that you can repeat without errors. It also tries to avoid having too many similar technologies or ways of doing things.
The main goal of XOps? To help businesses grow by being more flexible in design and quick to adapt, working well with other tech areas. This way, companies can really get the most out of their business and make things better for everyone involved.
6. Teams Will Make AI Work for Big Businesses
AI is becoming a big deal in business, like a special product made of data. After a big year for AI in 2023, 2024 is all about making AI really work in big companies.
Here’s the thing: AI shouldn’t just be for show. It’s not about adding fancy features to impress people. In 2024, teams will focus on making AI that's really useful for businesses, not just something that looks cool.
They'll be smarter about how they build AI. This means training AI in better ways and using it to solve real problems. The goal is to make AI that's not just smart but also really helpful and ready for big business challenges.
7. Data Fabric
Imagine a big, flexible network that can handle all sorts of data across different cloud systems. That's what a data fabric is. It's a smart way to manage data, making things standard and easy across various places where data is stored, like different cloud services.
As data gets more complicated, more businesses are going to use this method. Why? Because it can mix and match different ways of combining and using data. It’s like having a super-toolkit for all your data needs.
The best part? It cuts down the time it takes to design, set up, and look after data systems by a lot. This means less headache and less mess when dealing with data.
By 2026, think of data fabric like a service you rent, much like you do with cloud storage now. It's going to be a big deal to reorganize the way companies handle their data.
8. Big Data Going Small
Think about how much computers have changed. Today's laptops are as powerful as big servers used to be. This change is making a big difference in how we handle lots of data.
Most of the time, the data we work with isn't huge. So, data teams are starting to use special databases that work right where the data is being processed. These are called in-process and in-memory databases.
Why? They're easy to set up and start using. They're perfect for teams that need to move quickly and grow. Plus, with cloud services, these databases can become powerful enough for really big businesses. So, we're seeing a trend where handling big data doesn't always require big, complex systems. Sometimes, smaller and quicker solutions do the job just right.
9. Getting the Size Right with Data and AI
Data bosses have a tough job: use more data, make bigger things happen with AI, but at the same time, cut down on cloud spending. It's like being asked to bake a bigger cake but with less flour.
As of early 2023, money spent on cloud stuff went up a lot, reaching $21.5 billion. Every year, companies are spending up to 30% more on cloud services. That's a lot!
In 2024, smart moves like keeping an eye on metadata (data about data) and using tools to adjust how much cloud service you really need (right-sizing) will be super important. These approaches help teams not overspend while still getting the most out of their data and AI.
10. Rise of Apache Iceberg
Apache Iceberg is like a big, cool tool for storing heaps of data. It was made by Netflix's data team and is really good at handling massive amounts of information. You can search through it using SQL, even if you’ve got data as big as mountains.
Think of modern data storage places, like warehouses or lakehouses, where you store and work on data. Iceberg is all about giving you a good place to keep your data without costing a fortune. It works with many different tools your team might use, like Apache Spark or Hive.
Big names in data, like Databricks and Snowflake, are getting on board with Iceberg. This means they’re making their stuff work well with it. Since more and more companies are using lakehouses to manage their data, Apache Iceberg and similar tools are becoming super popular.
11. Heading Back to the Office, Sort Of
RTO, or Return to Office, is a hot topic these days. Teams have different views on it, but more and more people are being asked to come back to their office desks or open workspaces for a few days every week.
A report from September 2023 from Resume Builder says that by the end of 2024, 90% of companies will ask their employees to come back to the office. That's almost four years after everything changed in spring 2020.
Big bosses at companies like Amazon, OpenAI, and Google have already started making their teams come back to the office. And it turns out, there are some good things about being in the office at least part of the time instead of always working from home.
12. Data Observability Will Support AI and Vector Databases
In Amazon Web Services (2023) CDO Insights survey, respondents were asked what their organization’s biggest challenge was in realizing the potential of generative AI.
The most common answer? Data quality.
Generative AI is, at its core, a data product. And like any data product, it doesn’t function without reliable data. But at the scale of LLMs, manual monitoring can’t provide the comprehensive and efficient quality coverage required to make any AI reliable.
To truly be successful, data teams need a living, breathing data observability strategy tailored to AI stacks that can empower them to detect, resolve, and prevent data downtime consistently within the context of a growing and dynamic environment. And those solutions need to prioritize resolution, pipeline efficiency, and the streaming and vector infrastructures that support AI in order to be a contender in the modern AI reliability battle in 2024.
As we look towards 2024, it's clear that data and AI are playing a huge role in shaping how we work and do business. From data teams working like app developers to focusing on the quality of data for AI, things are changing fast. Large Language Models (LLMs) are transforming tech, while tools like RAG are becoming essential for smart AI.
Businesses are adopting XOps to make things run smoother, and AI is becoming crucial in big companies. We're also seeing a shift in how we manage big data, with tools like Apache Iceberg making it easier and more cost-effective.
But with all this technology, we can't forget about the people. The shift back to the office, at least part-time, is a trend to watch. And to keep all this tech running reliably, data observability is key.
In short, 2024 is shaping up to be a year where data, AI, and how teams work with them will be crucial. It's all about making sure these technologies are not just cool but really useful and ready for the challenges ahead.
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