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Wait, what is data management? And why does it matter so much?

Business intelligence. If you’re a cynic, you might call it an oxymoron. If you’re a true believer, you’ll call it the religion of the near future. If you’re a Luddite, you’ll just blink and go back to your abacus. Regardless of how you feel about the rise of Business Intelligence, or BI, in today’s highly connected digital workplace, it’s the lifeblood of entrepreneurs and Fortune 100 companies alike — and it lives and dies with the quality of your data management strategy.

Consider Big Data. You know, the semi-creepy amount of individual data points your company has access to today. You document your customers’ preferences, habits, and purchase histories. You may even keep track of the things they didn’t purchase but almost did. You can identify your target demographic down to their shirt size, favorite cuisine, or dating history. You can leverage tomorrow’s weather forecast and the spot rate of an Uber ride to grow your customer base. It’s all data. And the calculus on our data-driven future says the limit approaches infinity.

All that data, the overwhelming array of facts collected across our digital landscape, lays the foundation for business intelligence — leveraging deep data collections and AI to drive mathematically perfected business decisions. It all hangs in the balance of how good your data actually is. Can you really trust it?

Thus, data management was born and grew to become the heart and soul of 21st-century business intelligence. As the ancient aphorism goes, Garbage In. Garbage Out. And here’s the kicker, only the data manager truly knows the score.

What is data management?

A better question is, how do you ensure your team has the right data for the best possible outcome in data-driven decisions?

You manage it. Data management is about measuring and maintaining your baseline standards in the quality, quantity, visibility, security, and scalability of the data your organization values. To do this effectively and efficiently, you must build an infrastructure of data management platforms, your “tech stack,” that work 24/7 to make sense of these unprecedented quantities of data.

Data management is ultimately about ensuring your data's accuracy, availability, redundancy, and reliability as a vital business asset.

If you can’t trust it, no dice.

If you can’t get to it, game over.

If you can’t protect it, it’s not yours.

And, if you can’t confidently pilot your business’ future based on it, what are we even discussing?

Businesses like yours are making critical decisions today based on data they either don’t understand or can’t fully validate. That is the recipe for compromised business intelligence, also known as an unmitigated disaster. It’s not hard to see why data management is the fundamental business practice that separates tomorrow’s winners and losers.

Data management defined

Data management is often formally defined as “the process of ingesting, storing, organizing, and maintaining the data created and collected by an organization.” The strong verbs in this definition immediately provide a roadmap to the fundamentals of data management. Your goal is to ensure the data is accurate, available, and accessible at all times. It’s worth noting that there’s only so much the IT team can do here. Data governance policies are a critical component of data management because, for better or worse, there are always people involved in these delineated tasks. Creating a culture of good data management is every bit as important as identifying the right software, hardware, and IT leadership.

Data management in practice

Data Architecture is typically the cornerstone of a data management strategy. Everything else flows outward from the infrastructure of databases, platforms, and applications. As a blueprint for how the data flows within an organization, it provides the operating instructions for proper data management. With the proper architecture in place, you can identify choke points or bottlenecks. You can spot vulnerabilities and exploits. You can root out inefficiencies that compromise speed, quality, and performance. Understanding your data architecture is the first step to mastering data management.

Structured Data is the historical answer to data management. Essentially this is the concept of a series of databases that hold a collection of data organized in a particular fashion to provide transactional information. Built on SQL programming, these databases operate on a primary key that identifies each line of data as a unique component of the whole.

Think of sales orders or customer records. Things that exist in a linear fashion, like entries in a ledger. Their operating capabilities must be continually optimized to ensure queries are returned fast enough. These require maintenance and updates and backups. They also require significant oversight to ensure that, as a single point of truth, their current configurations are always up-to-date and accurate

There’s no dispute that databases are fundamental to data management, but we’re increasingly seeing something new win the day — Unstructured Data.

Unstructured Data is a NoSQL database that doesn’t require a rigid schema. In other words, you can collect, store, and access data from a variety of formats or file types in these databases. This ability to manage raw data is unprecedented in data management, and it gives rise to capabilities like data lakes — massive pools of data used to empower machine learning and predictive modeling. By storing information as objects rather than line-item entries in a traditional SQL database, the variety and volume of data available for analysis can elevate an organization’s capabilities almost instantly.

Why does data management matter?

Business intelligence is, by definition, a product of data. Therefore, the actionable quality of that output is driven by the effective quality of the data analysis. Insights don’t just happen — they’re the product of careful preparation and a keen understanding of causality and purpose. When done properly, an investment in data management can give your organization profound advantages:

  • Visibility: The more your people know, the more effectively and efficiently they can do their jobs.
  • Reliability: More insight into how your processes and policies perform corresponds to the perfectibility of your decision-making. Aim small, miss small.
  • Scalability: In an age of automation, repeatability is the gateway to scale. If data is the fuel for growth, duplication is the coefficient of drag.
  • Security: Cybercrime doesn’t sleep. Neither do natural disasters, hapless or hostile employees, and the entropy inherent in Newton’s Third Law. Considering your investment in developing your data, can you afford to risk this nearly tangible business asset?

The subsets of data management dial up the intensity of these concepts up to 11. Whether it’s navigating the specific regulatory compliance requirements and data privacy laws your team is subject to or empowering good data stewardship that ensures your entire organization adheres to data policies and procedures, the nitty gritty of data management is complex. Pitfalls abound.

Before you abandon all hope, consider that the future of data management is in the partnerships you build. Remember, your data architecture is the foundation of your data management. Building a technology stack around partners who understand both the risks and rewards of solid data management takes the burden off of you and puts it on the infrastructure. Good infrastructure can handle stress you wouldn’t even want to imagine.

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What’s the future of data management?

Let’s play a little futurist buzzword roulette. Hybrid cloud. Artificial intelligence. Internet of Things. Edge Computing. Deep Learning. Predictive analytics.

What do all of these things have in common? Solid fundamentals in data management. Without big data, none of these concepts would be possible. That’s why the data management ecosystem is alive and thriving. Next-generation technologies depend on data management as a fundamental concept — a non-negotiable. Clean, unified data is a baseline, not an aspiration.

Regardless of your industry, your comfort level with technology, and your understanding of just how valuable data is and will continue to become to your organization, leaders like bat365 can get you from data incompetence to business intelligence. It all hinges on data management. You want dashboards? You want widgets? You want automated, AI-powered interfaces? These all begin with data management. It’s the future of every business, and it’s a business fundamental that you don’t have to master to leverage. You just have to find the right partner.

Consider the case for a data management partner:

  1. Data volumes will only increase. Every second of every day, you collect more information. How that information is cataloged, cross-referenced, integrated into your systems, and protected will determine its availability and value to your organization. Even when you’re asleep.
  2. Analytics are evolving. Analyzing data is now the norm for team members in non-IT departments. If you don’t equip every member of your organization to navigate naming conventions and data storage procedures seamlessly, you’ll instantly diminish the value of your information and your organization’s potential.
  3. Data will never not be personal. Compliance regulations aren’t going anywhere. If anything, they’ll only get stronger. Protecting people’s identities and personal information is paramount to avoiding compromise. Or worse, penalization and investigation. Sound data management mitigates risk and reduces exposure, full stop.

Whether you’re a seasoned data analyst or a complete newb to the nuances of data storage and manipulation, it’s imperative that you understand the gravity of data management as part of your organization’s future. Without a proactive approach to data, you will quickly find yourself in a siloed mess that closely resembles quicksand. Every day you don’t improve your data management moves you one day further from success. You’ll mire yourself down in misinformation, misallocations, and misalignments. All it takes is a keen sense of respect for the value and sanctity of the data your organization possesses and a vision for how that data can transform your possibilities when properly managed. Data is the future. Do you have a plan to manage it?