Uncovering the secrets behind Big Data

Big Data is a hot topic in many industries including financial services. Emerging out of large Internet companies, Big Data only recently became applicable to other businesses. It addresses data and analytics challenges too complex for traditional, relational database engines to handle in a cost-effective way.

The bottom line? Big Data is faster, cheaper and easier to program than traditional platforms.  In this NICSA News webinar highlight, we share answers about Big Data from Paul Barth and Prithwi Thakuria of NewVantage Partners.

Big DataWhat is Big Data?

Big Data is a technology that addresses the four “Vs”:

  • Variety – Handles any kind of data, including unstructured data
  • Velocity – Rapidly ingests and combines a wide variety of data
  • Volume – Processes large volumes of data (i.e. exabytes)
  • Value – Allows construction of applications to extract value from data

What led us to the Big Data era?

Companies are seeking a cost-effective solution that:

  • Increases data accessibility
  • Improves data-driven decision-making (i.e. customer service needs)
  • Innovates using market and customer trends
  • Improves performance (i.e. risk management)

What’s behind Big Data’s power?

The engine behind Big Data is Hadoop, a core set of capabilities housed in a Java-based data management framework created by Apache. Hadoop supports the processing and computation of large data sets in a distributed computing environment.

How do you get started with Big Data?

Big Data is best introduced in analytical mode to address existing issues, i.e. extracting insights from data that had been difficult to integrate. By starting with a small problem and real data, you can best understand the opportunities and challenges of Big Data.

How much does it cost?

Need to consider:

  1. Hardware and software – Per terabyte cost is about $2,000 (as compared to $37,000 for traditional relational databases and $5,000 for newer appliances).
  2. Building a team – Key staff include: 1) a software developer; 2) a subject matter expert (mainframe programmer); and 3) analytical talent.

What are the challenges?

  • Governance, regulation, security – Clarity of ownership and access to data
  • Organizational change and talent recruitment – Finding a place for the Big Data team in the organizational structure
  • Creating a sustainable approach – Integrating Big Data to allow for evolution of the technology and addition of new analytics

NICSA members can listen FREE to the complete webinar and download the presentation through our online archives.

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