Big Data can provide tremendous value to your organization, but if you aren’t using data right, it isn’t going to do anything for you. From polling predictions that were way off to large retailers missing the mark, big data has had some big fails. The problem isn’t the data, though; it’s about the data quality and the people using it. In many cases, poor data quality is the result of rushing into a Big Data initiative, purchasing some Business Intelligence software, and thinking this will solve all your problems before doing the due diligence to create a good data set. This is the age-old axiom of “garbage in, garbage out” rearing its head once again.
Let’s start with a common understanding of the terms we’re dealing with…
Big Data refers to extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations. You’ve heard the term “Data Lake?” That is what you’re building with these large data sets. Business Intelligence is the actual analytical process of going fishing in your data lake. Getting to a good data set requires Information Governance, which refers to the process taken to get trusted information to the right people at the right time. There’s a lot in that last statement. Trusted information is a data set that is free of redundant, obsolete and transitory information – data boiled down to “the one version of truth.” The right people refers to a secure data source that delivers only what each person needs to do his job, and protects individual privacy as well as corporate intellectual property.
The most important thing to understand is that this is an ongoing process.
You start with Information Governance and build up to Big Data, which will lead to the ultimate goal of Business Intelligence. Information Governance begins with understanding the Four Ws:
- What do you have? (Identifying your organization’s information assets)
- Where is it located? (Hard copy and electronic)
- When can I get rid of it?
- Who owns it, maintains it and needs access to it?
Then you need to dig into your data, hard copy and electronic, and get rid of the redundant, obsolete and transitory information (ROT). All organizations have ROT to one degree or another that takes up storage space and makes it difficult to find the real information you’re looking for. The most important consideration here is that this is not a single person’s responsibility. It takes the active participation of people from Records Management, Legal, Information Technology and the Business to make this happen, and to maintain it over the long term.
Once you have cleaned your data, it’s time to build your lake! It’s important to keep in mind the current state of your infrastructure. Do you have enough storage? Are you moving some or all of your data to the Cloud? If so, what kind of bandwidth do you have now and what do you need for the future? Do you need to upgrade your electronic document management system? Most importantly is understanding the manpower you need to maintain these systems. All of these are critical points to know about before building a data lake.
Now you’re ready to go fishing!
Thankfully today’s business intelligence software offers Simplified Analytics and User-friendly tools without needing a data science degree. This allows you to put the power of business intelligence in the hands of people that understand your business and to find those quick wins so that you can gain value from your investment. A recent study has shown that 81 percent of organizations were successful in their big data initiatives that focused on the goals or opportunities to innovate while reducing expense levels. It is important to remember that this is just like any other organizational change and there are significant organizational issues, such as lack of organizational alignment, business and/or technology resistance or a lack of middle management adoption that must also be dealt with. The rewards of big data are very real and achievable with a clear plan that builds from a strong foundation in Information Governance and careful change management.