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Sorting Through Big Data’s Challenges Will Take Time

Big Data challenges Too Much Big Data Variety The variety of big data may not be the spice of life after all. In fact, 71% of the data scientists surveyed said new types of data make developing analytics apps more difficult. Biggest Big Data Challenge Big data analytics is more complex than most appreciate: 40% […]

Written By: Michael Vizard

Jul 15, 2014

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Big Data challenges

Too Much Big Data Variety

The variety of big data may not be the spice of life after all. In fact, 71% of the data scientists surveyed said new types of data make developing analytics apps more difficult.

Biggest Big Data Challenge

Big data analytics is more complex than most appreciate: 40% said they struggle with new types of data while 36% said it takes too long to get the answer they are seeking.

Types of Data Being Used in Next Year

Data comes in many structured and unstructured forms. Time series and business transaction data are tied, at 66%, followed by geospatial data, at 55%.

Plans for Big Data Analytics

The use of big data analytics applications is already pervasive: 59% have already deployed big data analytics and 31% plan to do so in the next two years.

Data Movement Issues

Big data tends to stay where it gets generated. One of the bigger issues for 36% of data scientists is that the amount of data that needs to be analyzed is too big for their organization to move into an application.

Limitations of Hadoop/Spark

Hadoop is only one element of the big data equation: 39% said Hadoop is too difficult to program while 37% said it’s too slow for ad hoc queries and 30% said it’s too slow for real-time analytics.

Hadoop/Spark Abandonment

Failure rates involving Hadoop are still pretty high: 37% of the data scientists who have tried Hadoop/Spark have abandoned it.

The Role of the Relational Database

Many organizations are outgrowing traditional relational databases. Just under half, or 49%, said they are having trouble fitting their data in a relational database.

Big Data Stress Factors

Much is asked when much is given. The growth of big data has made the job of being a data scientist more stressful for 39% of data scientists.

The Big Data Question

A knowledge of science does not always translate into business-savvy insight. Almost a quarter, 24%, said they don’t know what questions to ask when they gain access to all that data.

Michael Vizard

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a writer for publications including Programmableweb, IT Business Edge, CIOinsight, Channel Insider and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

Sorting Through Big Data’s Challenges Will Take Time

Michael Vizard

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