Analytics and Big Data Committee

Welcome to the Analytics and Big Data Committee (ABDC)!

The ABDC is a SNIA Committee that is dedicated to fostering the growth and success of the market for what is generally referred as Analytics and Big Data, and more generally, the use of data storage resources and services by analytics and big data applications and toolsets.  If your company is a SNIA member, there is no fee to join and participate!

The ABDC mission addresses marketing outreach, education, and collaboration with other industry bodies relative to Analytics and Big Data efforts. Also, the ABDC will closely follow of the advancements in Analytics and Big Data science, product offerings and business models from academia, industry and the research community.

To fulfill this mission, the Analytics and Big Data Committee is organized around the following goals:

  • Become the recognized authority regarding the use of storage and storage networking for Analytics and Big Data
    • Determine and document the characteristics of Analytics and Big Data offerings
    • Determine and document the impact of Analytics and Big Data on enterprises and analytics and big data computing
    • Collect requirements from Analytics and Big Data vendors and document best practices in this area
    • Collaborate with academia and the research labs of member companies to understand how advances in storage, storage networking, and other technologies will affect Analytics and Big Data
  • Educate the vendor and user communities on the use of storage and storage networking for Analytics and Big Data
    • Coordinate education activities with the Education Committee
    • Create peer reviewed vendor-neutral SNIA Tutorials
    • Create vendor-neutral demonstrations
    • Leverage SNW and other SNIA and partner conferences
    • Collaborate with industry analysts
  • Perform market outreach that highlights the virtues of storage and storage networking for Analytics and Big Data
    • Articles in trade magazines
    • White papers
    • Press releases
    • Collaborative published articles with academia and research institutions
  • Collaborate with other industry associations via SNIA’s various strategic alliance partners on analytics and big data related technical work in which they are involved
  • Coordinate with SNIA Regional Affiliates to ensure that the impact of the Analytics and Big Data Committee is felt worldwide
  • Coordinate with the Cloud Storage Initiative to jointly message the Analytics and Big Data cloud-oriented market and offerings

The ABDC has an initial set of five member companies, in alphabetic order: EMC, HP, Huawei, NetApp and SpectraLogic. The chairperson of the ABDC is Gilda Foss (NetApp) with Molly Rector (DataDirect Networks) serving as vice-chairperson.

Featured Article: Big Clouds Full of Data

CLOUD COMPUTING and big data analytics go hand-in-hand and are on the forefront of the minds of IT professionals today. As a delivery model for IT services, cloud computing has the impending ability to enhance business nimbleness and productivity while enabling larger efficiencies and reducing costs. Big data analytics offers the assurance of delivering valued insight that can create a competitive advantage, inspire new innovations, and drive more revenue. Read full article here.

Featured Tutorial: NextGen Infrastructure for Big Data

The internet has spawned an explosion in data growth in the form of data sets, called Big Data, that are so large they are difficult to store, manage and analyze using traditional RDBMS which are tuned for Online Transaction Processing (OLTP) only. Not only is this new data heavily unstructured, voluminous and streams rapidly and difficult to harness but even more importantly, the infrastructure cost of HW and SW required to crunch it using traditional RDBMS, to derive any analytics or business intelligence online (OLAP) from it, is prohibitive. To capitalize on the Big Data trend, a new breed of Big Data technologies (such as Hadoop and others) many companies have emerged which are leveraging new parallelized processing, commodity hardware, open source software and tools to capture and analyze these new data sets and provide a price/performance that is 10 times better than existing Database/Data Warehousing/Business Intelligence Systems. Download tutorial (pdf, audio{20MB}).