Big Data. What is it? Those of us who have helped organizations improve competitiveness through more effective use of information know that most data has value. The trick is in defining that value, determining how best to get at it and then executing a process to extract it. Every few years it seems we have to create a rally point for more focus on just how impactful information is, and for the past several that rally point is Big Data. If you believe what you read and hear, it can be pretty much anything you want it to be. But there is at least one shred of truth in what we call it; it is BIG.
Is your organization ready for Big Data? You may already have invested in data warehousing and business intelligence. You may already have tools in place to deliver information to your business processes and users. But Big Data promises an avalanche of more variants from more sources, more often. Are your existing environments, processes and methods up to the challenge? Will your business analytics get the right fuel to unleash the value in Big Data? When it comes to winning with Big Data will you be a leader or laggard?
For all its hype, Big Data is still just that – data. And its value will be tied to how well and how quickly your business exploits it. The simple truth is that today it takes too long for most companies to quickly integrate new sources of data for business analytics and reports. In fact, our surveys of data warehouse users and operators show that nearly 30% of organizations take over 90 days to integrate those sources, and almost 40% take 1-3 months. That is today. As data volumes, variants and velocities – three of the elements of Big Data – increase, common sense tells us those numbers don’t get better.
Getting your organization ready for Big Data, however you define it, is important. Starting to get ready now is not a bad idea. But what should you be thinking about? We believe there are three keys.
Put your house in order
You already know that if your enterprise can’t use information effectively and efficiently, you are at a disadvantage. Market research firm Gleanster found in a recent study that over 70% of top performing companies can integrate new data into reports within a week. Only 20% of low performers can match that. Data that can’t be quickly integrated can’t be used by the business when it is most relevant and able to create peak value.
Improving this means getting your data warehouse and master data houses in order, and ensuring they can be updated quickly are key enablers to extracting full value from Big Data. Ignoring this means you start at a competitive disadvantage that only worsens over time.
Only manage what matters
Have you established an iterative and collaborative culture between Business and IT? Why do we ask? Using your customer/product/material data, processes and performance indicators as a business-value lens helps prioritize what Big Data is relevant and lets IT professionals establish processes and structures to mine only the most relevant. Insights from Big Data are only useful if your organization can directly relate it to sales performance, customer satisfaction, on-time delivery performance, financial performance and other key business outcomes.
With the deluge of data coming, it’s a certainty not all of it will be worth retaining or managing. Market leaders will put Business and IT professionals at the same table to determine what data is relevant and invest to automate methods linking it to business analytics. Mining the value of Big Data is a sustained, iterative process between Business and IT, and the only way to make informed tradeoff decisions on where to invest.
By their very nature, the opportunities to exploit business value in Big Data will be transient and require speed of response. There can be tremendous value but capturing it necessitates a more agile way of working. An agile data foundation for automated analytics is your objective.
The first step toward that foundation is Business people and IT professionals iteratively designing a model that provides context for the introduction of relevant Big Data to core business processes and metrics. It continues by assuring the model is flexible and may be extended to incorporate new, unforeseen sources that can deepen insights. And finally, it means the model can be modified in hours or days while new data is freshest and most relevant.
Where does that leave you?
The best way to get ready for Big Data is to prepare now. To get started, look for model-driven, agile data warehousing and master data management technology to enable you to deliver a high-quality, fully governed foundation for Big Data analytics quickly, using tools that foster strong Business & IT collaboration.
Much of the data used for this article came from Gleanster’s new report “How Agile Data Management Enables Faster, Smarter Business Decisions”. We’ve made arrangements to offer you this report for free. Simply click the button below.