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The Business Problem

The first thing to consider when starting an analytics practice is your core business. Are you in manufacturing or healthcare? Are you a service provider or a pharmaceutical startup? Below are a few examples that show how data analytics could benefit certain industries.

  • Manufacturing: If you are in the business of manufacturing, there are several problems that data analytics can help with, including increasing productivity, reducing labor costs, and preventative maintenance. Predictive maintenance allows preventative maintenance to occur. With the ability to gather, store and process data coming from various equipment, software can perform correlations and can observe trends that can predict when equipment might need preventative maintenance. To perform this kind of analytics, a company would likely need to gather and store all available data points from all available equipment.
  • Software: Many software companies want to understand how customers use their products. If a company’s product can generate statistics on usage – as most apps do today – then it can collect, store and process this data to gain analytic insights. For example, companies can correlate usage data with social media information to understand if customers engage with people to discuss how much they like or dislike the company’s product. This particular analytic can help companies tailor marketing campaigns based on customer sentiment.
  • Start-ups: A start-up in the human resources analytics space is effectively in the analytics business. Or maybe a company is building the next wiz-bang social media platform, which almost necessitates that the company will use analytics to help drive content and user behavior on its platform.

At Secureworks, our core business is to provide Managed Security Services. Our primary goal is to provide intelligence-driven security solutions and expertise to our clients. In 2012, we saw a need to form a data analytics team to design and build a new product. Our service delivery platform consumes as many as 240 billion events day and leverages our intelligence gained over 18 years of processing and handling events. Therefore, we have a lot of data we can use for research, prototyping and development.

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Read more here:: CIO.com

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