Advertisement
Singapore markets closed
  • Straits Times Index

    3,272.72
    +47.55 (+1.47%)
     
  • S&P 500

    5,010.60
    +43.37 (+0.87%)
     
  • Dow

    38,239.98
    +253.58 (+0.67%)
     
  • Nasdaq

    15,451.31
    +169.30 (+1.11%)
     
  • Bitcoin USD

    66,172.88
    +216.06 (+0.33%)
     
  • CMC Crypto 200

    1,421.94
    +7.18 (+0.51%)
     
  • FTSE 100

    8,044.60
    +20.73 (+0.26%)
     
  • Gold

    2,311.20
    -35.20 (-1.50%)
     
  • Crude Oil

    82.22
    +0.32 (+0.39%)
     
  • 10-Yr Bond

    4.6230
    +0.0080 (+0.17%)
     
  • Nikkei

    37,552.16
    +113.55 (+0.30%)
     
  • Hang Seng

    16,828.93
    +317.24 (+1.92%)
     
  • FTSE Bursa Malaysia

    1,561.64
    +2.05 (+0.13%)
     
  • Jakarta Composite Index

    7,110.81
    +36.99 (+0.52%)
     
  • PSE Index

    6,506.80
    +62.72 (+0.97%)
     

Qubole Releases 'State of DataOps' Report

The new survey reveals big data initiatives at risk due to high demand, false confidence and immature processes

SANTA CLARA, CA--(Marketwired - Mar 9, 2017) - Qubole, the big data-as-a-service company, today announced the results of its State of DataOps report -- a survey of IT and data professionals on the progress of their big data initiatives. The survey revealed a clear reality gap: while data teams have high confidence they can enable self-service insights to meet growing demands across the enterprise, few have delivered on that promise.

According to the survey, 76 percent of respondents said their company currently has a big data initiative, and another 20 percent said they plan to soon. In addition, 93 percent of respondents said business demand for big data analysis is growing.

Sixty-five percent of IT teams recognize that to get to ubiquitous access to data and analytics, they need to enable a self-service DataOps approach. And most respondents -- 87 percent -- felt confident to extremely confident that they could deliver self-service analytics.

Yet, respondents characterized their big data processes as still in the earliest stages of maturity: only 8 percent of respondents consider their big data initiatives to be fully mature.

ADVERTISEMENT

A deeper dive reveals that IT is besieged by operational and technological challenges that interfere with improving big data maturity:

  • Only 12 percent of respondents said they have multiple big data projects running

  • 98 percent said they face numerous challenges with their big data initiatives

  • 78 percent still support data requests on a project-by-project basis

  • 45 percent can't satisfy business needs and expectations

  • 61 percent rely on third-parties for big data expertise

"Having experienced this firsthand at Facebook, delivering on the promise of self-service access to data and analytics across the enterprise is extremely difficult and goes way beyond technology, involving rethinking processes, company culture and the operational model of the data team," said Qubole founder and CEO, Ashish Thusoo. "Until IT teams adopt a DataOps approach versus a more traditional command-and-control model, they'll remain a primary bottleneck to insights and their big data initiatives will continue to struggle. But there is a path -- some companies have successfully made the transformation, and others can learn from their experiences."

Additional findings:

Data analytics is moving rapidly to the cloud:

  • Nearly six in 10 companies are currently using at least some cloud resources for big data processing: 14 percent are running all big data processing in the cloud and 41 percent are running at least some data processing in the cloud

  • Another 30 percent of respondents say that while they are currently running big data processes on-premises, they are considering cloud as a future option

  • Amazon Web Services (AWS) leads the pack, with 32 percent of respondents saying they use Amazon's cloud platform for big data processing. Microsoft Azure, however, is not far behind, with 26 percent of respondents using it for big data projects. Google Cloud Platform is used by 12 percent of respondents and Oracle Cloud is used by 11 percent

Businesses are in need of big data expertise:

  • 83 percent of respondents said their data teams are growing

  • 36 percent of respondents said they are having difficulty finding people with expertise in big data projects

  • 31 percent said there aren't enough technical resources to run big data operations effectively

  • 61 percent of respondents reported that their organization uses third-party consultants with big data expertise

Resources
Download the full report, and register for the accompanying webinar diving into the results, featuring David Gehringer from Dimensional Research and David Hsieh from Qubole.

Register for Data Platforms 2017, the first industry conference dedicated to helping data teams build the modern big data platform based on the experience of data pioneers such as eBay, Google and LinkedIn.

Pre-order O'Reilly Media and Qubole's soon-to-be-released book, "DataOps: How to build a self-service data platform."

Research Methodology
The research report, commissioned by Qubole and conducted by independent research agency Dimensional Research, polled 406 IT and data professionals globally. The survey was administered electronically and participants were offered a token compensation for their participation.

About Dimensional Research
Dimensional Research provides practical market research to help technology companies make their customers more successful. Our researchers are experts in the people, processes, and technology of corporate IT and understand how technology organizations operate. We partner with our clients to deliver actionable information that reduces risks, increases customer satisfaction, and grows the business. For more information visit www.dimensionalresearch.com.

About Qubole
Qubole is a big data-as-a-service company that provides a fast, easy and reliable path to turn big data into valuable business insights. Qubole's cloud-based platform addresses the challenges of processing huge volumes of structured and unstructured data. It uses clouds such as Amazon Web Services, Google Compute Engine, Microsoft Azure and Oracle Cloud Platform to help enterprises extract value out of their big data while enabling their operations teams to be nimble and adaptive to their users' needs. Qubole achieves this through features such as auto-scaled big data clusters and integrated toolsets for data analysts, developers and business users. With more than 500+ PB of data processed every month across its customer base, Qubole's platform makes enterprises agile with big data.