For many companies, current methods of collecting, interpreting and assessing data are actually hindering their efforts to extract actionable details.

The expansion of data in business operations has been unfolding for decades, but it’s only been within the past few years that organizations have really started embracing Big Data as in integral part of strategic planning and operations. In the age of social media and digital devices, there’s no shortage of customer information for companies to glean. For many companies, however, current methods of collecting, interpreting and assessing data are actually hindering their efforts to extract actionable details. Staff and decision-makers alike often feel that they are spinning their wheels, working diligently toward KPIs and other objectives but making little forward progress.

Overcoming this challenge isn’t easy, but reliable data evaluation, insightful data exploration techniques and knowledgeable advice can go a long way toward making the changes necessary for a true digital transformation.

Analytics

Analytics encompasses all of the data processing, number crunching, trend identification, solution comparisons and other assessments that must occur before intelligent business decisions can be made. It also includes data visualization to provide a more concrete, intuitive understanding of what you’re working with than spreadsheets or reports.

This is when you break down the data to determine why things are happening as they are and what you can do about it. In short, analytics is about asking questions:

  • Who are we not reaching effectively?
  • What is hindering our expansion into the digital arena?
  • Where should we focus our technological transformation efforts?
  • When is the best time to implement changes?
  • How do we know we’re on the right path?

The same data that answers questions about the past and present can also be used to foresee the future. You can run predictive analytic simulations that can determine how a course of action will turn out. These complex algorithms skim historical data, find patterns and then calculate the likelihood of certain outcomes. The resulting models can give you a good indication of whether an avenue is worth pursuing or if your strategy needs to be tweaked. This increases the level of informed decision-making significantly and puts your organization back in control of its data.

Data Mining

Data that seems insignificant now can actually have a huge impact when it’s paired with other information. Data mining is all about searching for these little bits of information to reveal trends and tie together seemingly unrelated items. One of the most famous examples of this concept is the Osco Drug study conducted in 1992 that found a correlation between the purchase of diapers and beer. The idea was that spouses who were sent to the store for diapers often picked up a few beers as well. Osco moved their diapers and beer closer together and saw a marked increase in the sales of both — often together.

This form of business intelligence is an area of analytics, but it does have some distinct qualities. Data mining is more searching than measuring. The main idea is to see if two or more things fit together, not necessarily how. It basically involves looking for answers to questions you’ve yet to ask, sifting through the static of transaction data, clickstream info, server logs, social media activity, market reports, customer communications and other aspects of the Internet of Things to find discernible signals.

Big Data Consulting

Big Data and the advanced analytics that accompany it are revealing exciting new avenues for businesses to increase their efficiency across the organization, improve customer experiences and boost revenue. But having the data at your fingertips is the easy part. It gets trickier once organizations realize that they don’t have the in-house skills to fully leverage the data into something they can really use — nor do they have the budget to hire the necessary level of talent.

This is why good big data consulting providers can be one of the most powerful tools your company can use. These teams of advisers are usually made up of data scientists, modelers and architects, as well as other business intelligence and management specialists. This mix of strategy and data expertise can help you evaluate your current data assets, people power and technological capabilities, measuring them against your future goals and ensuring that your businesses is working in the right direction with the proper resources. Data advisers can help your company dissect its Big Data to help reveal trends, correlations and weak spots that may be overlooked by the untrained eye, then help you map out a plan for implementing upgrades in these areas. You’ll also realize a distinct advantage over competitors that have yet to employ the expertise of a Big Data professional in their business strategy.

Most importantly, you can often realize the benefits of a full-time Big Data employee for a fraction of both the time and the cost. Consulting can be done on an as-needed basis with assistance coming in the form of simple advisory roles, facilitators of large projects and key tasks, or even an entire team of professionals that completely take the reins.

As the reach of Big Data continues to expand, organizations are finding more and more reasons to incorporate heavier equipment in their technological arsenal. Analytics and data mining are two of the most effective weapons you have against stagnation when it comes to business intelligence, but smart consulting ties it all together. Using these tools to enhance your understanding of Big Data will promote the evolution of data from an asset to a strategic decision-making tool.