How to Make Sense of Big Data Analysis & Spreadsheets
You’ve read the latest blogs. You’ve attended the conferences. Big data has cemented itself as a core part of many companies’ strategies because of its immense value in today’s competitive environment. Big data can provide insights that have the potential to make or break a business, and that’s no longer an insider secret.
So, now that everyone is collecting this big data, the question remains: After it’s extracted, how do you make sense of it?
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Being Proactive vs Reactive With Your Data
Approaching analysis within big data proactively is the best way to set yourself up for success. With a disciplined approach and understanding your plan and strategy apart from simply collecting data will greatly increase your likelihood of success. Without connecting and correlating relationships or hierarchies, your data can become unmanageable quickly.
For many companies, that responsibility falls on a relatively new position: the data officer. This person is tasked with overseeing the utilization of information as an asset, typically via data mining, processing, and analysis.
Turning data into information and information into intelligence
Making sense of big data is similar to making sense of any sort of external data, just on a different scale. When dealing with high-volume, high-velocity, and/or high-variety information assets, you still want to remain cost-effective and drive decisions.
A common example sees the data flow upward from various data sources and pass through data stores. From these stores, the data reach you’re reporting and analysis tools, sometimes in the form of spreadsheets.
Some data might come through in manageable sizes where you are simply able to make judgements without too many steps.
But oftentimes, your queries can result tens of thousands of rows.
These spreadsheets may seem daunting. Rows upon rows and columns upon columns — but this is all valuable. Unfortunately, while big data has grown, the human capacity for processing this raw information in a timely manner has not.
With big data, a great way to address the challenges you might face due to scale are your tools. Repeatable cleaning and transforms helps keep your data manageable. Some tools even analyze your data and present you with several table options.
Get to know your tools
These big data tools cover a wide spectrum of complexity. Reporting tools tells you what happened. Analysis tools tell you why something happened. Monitoring tools tell you what’s actively happening. Forecasting tools guess what might happen. Predictive tools tell you what will probably happen. Prescriptive tools can even tell you what sort of actions to take.
Big data doesn’t have to be intimidating. Approach it with flexibility and understanding of what your tools are doing, and you’ll be on your way to making decisions with confidence.