First, if you’re a human of data – aka someone who works with data for a living – here’s your virtual medal. 🏅🏅🏅
Why? Because we know how frustrating it can be to manage data and all its appendages, from metadata to data lineage and beyond! Now we know we can’t wave a magic wand and wish it all away 🔮 (Hmmm, or can we? Scroll to the bottom to find out!).
But, in the meantime, we can make it easier for you to navigate the data verse. That’s why we’ve created this super simple guide to help you understand the basics of data management and more importantly, understand the best approach to managing your data.
Without any further ado, here’s data management 101: five things you should know.
#1 What is data management?
If you’ve ever Googled this term, you would have realized—the more you Google, the less you know. That’s because data management is a very vast field with ever-changing definitions and scope. Just like urban slang or dance moves (dab, anyone?).
But, we can all safely agree that at its basic, data management is the management of data throughout its lifecycle in an organization—from data ingestion and discovery to data analysis and governance.
This means that data management has a pretty large scope. It can include all the policies and procedures that specify how data will be treated across all its touchpoints within a company.
Need the experts to weigh in? Well, here you go.
Data management (DM) consists of the practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes.Gartner Glossary
Incidentally, data management shows up as one of 9 trending terms on the Gartner Glossary. 😎 Now that you’ve understood the basics, let’s dive into the depths.
#2 How does data management help you?
A solid data management strategy and platform will help you manage data at every step and for every use case by giving you the following capabilities:
Data integration: Struggling to ingest data from diverse sources, formats and types? Or still need to loop in your data and infrastructure engineers every time you need to ingest petabytes of data? Data management can help you do all this without breaking a sweat.
Data catalog: Still find it a nightmare to discover, share and collaborate on your data assets? By setting and following healthy data management practices, you can boost the discovery and visibility of the data that you already have.
Wondering how data catalogs can help your team boost data discovery and access? Read this article for all the answers you need. Or see a data catalog platform in action here.
Data analytics: Do business users in your company frequently complain about how it takes them forever to get the data they need or get the insights they requested? All this can be a thing of the past with modern data management practices.
Data governance: Is it really possible to collaborate on data while ensuring its security and integrity? Yesss! Solid data management practices can help you work with data and stay on the right side of the laws of the land.
Looks all hunky-dory then, right? Nope! Here’s the twist in the story…
#3 What are the biggest challenges in data management?
Data has become the new oil, the new currency, the new moat and what not.
This means that the business is now realizing the tremendous value of data and making data-driven decisions. So naturally, data and analytics leaders have to manage and accommodate diverse business requirements—from data scientists building complex models to business users running simple SQL queries.
But at the same time, they have to manage data governance and compliance enterprise-wide. That’s a daunting task for any CDO or analytics leader.
The two biggest challenges in data management are centered around data catalogs—finding and identifying data that delivers value, and supporting data governance and data security.Gartner Data Management Strategy Survey 2017
Given the diversity of use cases that could present themselves, it’s clear that there’s no point setting up your data and metadata management to suit only one use case. You need to adopt a data management strategy that lets you cater to an infinite number of possibilities of what data can do for you and your team.
The bottom line?
Changing requirements from both business and IT are driving demand for data quality tools, data catalogs, metadata management solutions and data integration tools in one comprehensive solution, according to Gartner.
#4 What does the writing on the wall say when it comes to data management?
The message is loud and clear. 📢
Instead of adopting data management tools that solve only specific use cases, companies must adopt a data management platform that integrates data discovery, access, analytics and governance in one place. This will help them create a modern data management infrastructure that goes beyond the siloed approach of traditional data management tools.
To succeed with data and analytics initiatives, enterprises must develop a holistic view of critical data management capabilities… Demand for data management capabilities has translated into demand for convergence of capabilities across data management tools and solutions.Gartner research
#5 How can Atlan help when it comes to data management?
As seen above, most data management tools end up creating more data silos than removing them. With Atlan, you can create a data management infrastructure that helps you manage data discovery, access, analytics and governance in one place.
We help you manage data across its lifecycle with a human-first experience that teams will actually enjoy. Here’s how:
Integrate data from multiple sources into a single, unified view
- You can import and combine data from multiple sources, formats and tools, including streaming data, in just a few clicks.
- Yep! We’re talking about ingesting petabytes of data without any IT or engineering support.
- Your data is always updated with our change data capture capabilities and you can keep bad data out of the system by running data checks, deduplication, etc. right at the time of ingesting data.
Boost data discovery and access via our data catalog
- You can create a single course of truth for your data across your data ecosystem.
- You can easily find the data you need by filtering by owner, status, team, timeframe and more, and bring your human tribal knowledge alongside your data (README summaries, crowdsourced data ratings, status tags and more).
- You can even give your data its own profile—replete with a data dictionary and quality reports—and make it shareable via a single URL.
Make it easy to explore and experiment with data
- You can create a self-service analytics ecosystem where data explorers and data pros alike can explore data, run and save queries and code, and apply complex transforms to their data via an easy-to-use graphical interface.
- Or run advanced analytics within Atlan by running R or Python scripts or our notebook integrations.
- You can also easily share insights via integrations with PowerBI, Tableau and many more.
Find a balance between data access and data security
- You can simplify data governance and compliance by defining granular access policies and permissions, as low as cell-level.
- You can trace the history of your data and review all changes made to data and roll back to any previous version.
- You can understand and boost data adoption by understanding who is using your data, such as most used workflows and users with most queries.
But full disclosure—we might just have a maker’s bias when it comes to Atlan! So we’d love to hear what you think of Atlan. Request for early access to Atlan here.
And that’s it! Now go forth and manage your data like a pro!