Companies are pouring vast amounts of resources into big data and the tools used to collect it. However, many have yet to see a tangible payoff from these investments. That’s because big data shows you overall trends and patterns. It only offers a view of the landscape, whereas small data shows you the best places to grow on that landscape. To extract the truly valuable bits from your company’s data, you need reliable and robust analytic capabilities to determine what small data is most important. This information will vary from business to business based on location, industry, target consumers, and company culture.
Big data is cumbersome, and it’s difficult to discern what’s useful and what isn’t. Sometimes the most useful, pertinent data is hidden at first. Small data analytics add clarity to the patterns within big data. Your analytics teams must be able to connect small data to the big picture to make it actionable. But sometimes, separating the truly valuable metrics from the fluff is a challenge.
Data itself is not inherently useful; the value of data rests in the insights gained from it. This requires a deep understanding of the connections, context, and reasoning for those connections. Essentially, big data provides the “what,” and small data answers the question of “why.” Many methods exist for extracting valuable data from the vast pools of big data that companies are gathering. Computer programs, artificial intelligence, and advanced analytical tools will all make a difference in how business leaders leverage data to drive their companies into the future.
Artificial intelligence presents an unprecedented opportunity for data analysts to quickly find and extract the valuable data points. Google Analytics allow you to see important trends in your data, but you must never discount the value of human analysis. AI and computers may be able to find the patterns, but human insight distinguishes how those patterns matter to an organization.
Analytic tools like those from Google can also detect anomalies in your data. Again, having access to this information is important, but what you do with it is far more critical to your business. It takes a human eye to determine where the pain points lie, and how to use the data as a cost-effective decision-making tool.
This means finding a balance between small data and big data. Gathering very specific metrics over time—and on an individual basis—isn’t a very cost-effective means of gaining insight. The value of big data also increases with volume. Collect as much data as possible, then extract the smaller patterns that matter most to your company.
To sum things up, how big data is used will vary from business to business. The most valuable pieces of small data will highlight the best ways to leverage your data as a decision-making tool. This is going to require a robust data-collection system, reliable analytic software, and experienced professionals who understand the nuances of your organization. Finally, the leaders of your company must know how to use the insights gained to the benefit of your organization.
The importance of data won’t diminish anytime soon—especially in the face of the digital transformation encompassing virtually every modern business. Data is one of the most valuable commodities in today’s world, and collecting as much pertinent data for your company is absolutely critical. However, what is far, far more important than data collection is what you do with it. Big data offers a broad view of all the possibilities in front of your organization. But small data tells you exactly how to seize them.
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