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Posted: Oct 9, 2015
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4 Big Data Business Challenges

The Challenges of Big Data

Often Big Data has been talked about as a “problem” because it couldn’t be easily processed with traditional systems based on relational databases, but it really is a tremendous opportunity to enhance and even transform how you run your business. The value of Big Data can be significant.

It can lead to innovations, such as new pricing models, new ways to engage with your customers and partners, new product ideas, or new market opportunities. For example, at a recent conference, one large financial institution estimated that Big Data could help them reduce by 30-65% the time to market and cost of their strategic innovation projects.

According to Gartner Research, Big Data can have a major impact on your current business in three ways. It can help you: 

  • Discover Hidden Insights—If you consider customer survey data when investigating a high service cancellation rate, you may detect a pattern or root cause that wasn’t visible before and that you can eliminate to improve retention.
  • Improve decisions, by enriching information for decision makers—If you consider a customer’s social media profile, you can get a clearer picture of that customer and their place in the world and you can use that information to improve your response to service inquiries or to prioritize fraud alerts.
  • Automate business processes—you can look at detailed stock trading information to identify patterns that lead to poorly executed trades and automate the process so that certain steps are taken when that pattern occurs again.

When considering your Big Data projects and architecture, be mindful that there are a number of challenges that need to be addressed for you to be successful in Big Data and analytics. Below are the the top four Big Data challenges:

1. Data Integration 
The ability to combine data that is not similar in structure or source and to do so quickly and at reasonable cost. With such variety, a related challenge is how to manage and control data quality so that you can meaningfully connect well understood data from your data warehouse with data that is less well understood.

2. Data Volume 
The ability to process the volume at an acceptable speed so that the information is available to decision makers when they need it.

3. Skills Availability 
Big Data is being harnessed with new tools and is being looked at in different ways. There a shortage of people with the skills to bring together the data, analyze it and publish the results or conclusions.

4. Solution Cost 
Since Big Data has opened up a world of possible business improvements, there is a great deal of experimentation and discovery taking place to determine the patterns that matter and the insights that turn to value. To ensure a positive ROI on a Big Data project, therefore, it is crucial to reduce the cost of the solutions used to find that value.

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