A recently released survey demonstrates the reluctance of many IT professionals to adopt Dig Data strategies. The survey specifically addresses the adoption of Apache Hadoop because of the “sizable challenges around business value and skills.” Because Apache Hadoop represents the most popular tool for processing Big Data, the survey indicates a much larger problem for adopting Big Data tools. The key is to get the most business value from Big Data, which is easier said than done. However, forward-thinking IT professionals are working hard to get a more accurate idea of how customers behave, which helps them extract optimal business value from using Big Data tools.

What is Big Data Analytics?

Big data analytics represents a highly complex process of analyzing Big Data to reveal critically important information, such as identifying concealed patterns, correlations, market trends, and consumer preferences. Acquiring this type of information helps organizations of all shapes and sizes make much better-informed business decisions. Looking at it from a broader perspective, data analytic techniques and technologies provide companies with a more effective way to examine sets of data, as well as obtain new information. Business Intelligence queries answer the standard questions asked about business performance and operations.

Big data analytics is a form of advanced analytics that work with complex applications that include elements such as predictive modeling and statistical algorithms.

How Does Big Data Analytics Work?

Big data professionals gather data from a wide variety of sources that are a blend of structured and unstructured data. The data sources include cloud and mobile applications, as well as web server logs, and social media content. Then, data scientists prepare and process the data, which is stored in a data lake or data warehouse. Data scientists organize and configure the collected data for analysis before cleansing the data to enhance its quality. The data gets “scrubbed” by using scripting tools or data quality enhancement software.

Finally, analytics software analyzes the data, with some of the applications including data mining, machine learning (ML), and artificial intelligence (AI).

How to Maximize the Value of Big Data for Your Business

Maximizing the value of big data for your business boils down to doing four things right.

Address a Business Problem

Big data is useless unless you identify a business problem to solve. Scouring through the vast amount of data with Hadoop or another type of advanced analytic tool can be enjoyable for data scientists, but it also can be a huge waste of time for front-line managers that are not able to correlate big data with solving a business problem. Focusing on one business problem at a time helps your organization identify helpful data sources, as well as select the right big data tools and techniques.

Implement the Most Recent Analytic Innovations

Rapidly changing innovations associated with Business Intelligence (BI) and Business Analytics (BA) are changing the way businesses provide value for their customers. The rapidly changing innovations in BI and BA have triggered a shift from traditional approaches that generate periodic performance snapshots, such as descriptive reports and historical dashboards. The shift has created systems that constantly analyze incoming big data to present insights, which are actionable insights unfolding in real time.

Maximizing the value of big data allows your business to become much more agile when interpreting data.

Use Different Analytic Tools

Ask a data scientist to choose a favorite analytic tool, and you should receive a quick, enthusiastic response. Although leaning on one type of analytic tool puts IT professionals in a comfort zone, one of the keys to maximizing the value of big data analytics for your business involves diversifying the use of analytic tools. This helps your organization to reap the different benefits delivered by analytic tools such as SQL, SAS, Hive, and Python. Waiting for your favorite analytic tool to play catch up to technological advancements is not a feasible strategy in the rapidly changing world of big data analytics.

Optimize the Advantages of Cloud Computing

Once upon a time in the world of information technology, an organization had to make a substantial investment in expensive infrastructure to process big data. An organization also had to use financial resources to recruit the type of talent that could quickly learn specialized skills.

Cloud computing has changed all of that.

When you run big data analytics through the cloud, a dedicated third party manages the appropriate systems and services to give managers more time to address the current business problem. Cloud computing is secure, reliable, and even environmentally sustainable.

The Bottom Line: Give Control to the Right Business Experts

The final tip on how to maximize the value of big data analytics for your business might be the most important. Your job as an IT professional is to give the business experts in your organization insights that allow them to refine and implement high-performance strategies.

Give your organization’s business experts the data they need, and then let them run with it.