Goldilocks guide to Enterprise Analytics

Goldilocks guide to Enterprise Analytics

We all remember the story of Goldilocks and the 3 Bears. Through the process of elimination Goldilocks eventually finds an option that is “just right.” When it comes to Enterprise Software, companies have to go through the same bad experiences, but they often don’t find an option that is “just right.” Unfortunately for most organizations, it's too difficult (and too expensive) to fully go through this process of elimination. Not that organizations don't try, there are demos, POCs, RFPs, and pilot programs. However, none of these attempts allow companies to see the end result over an extended period of time. So especially in the analytics space, we end up finding that the sexiest and most interactive user interface wins the prize, only to find out later that there are major technical holes which keep it from being adopted company wide or for big datasets.

For Intricity (the consulting company I work for) we get to experience the full Goldilocks process of elimination by being introduced to new organizations on a consistent basis. This opportunity provides us a unique view into the shortcomings of certain approaches for turning data into information. In this white paper, we’ll share a couple things Goldilocks would have noticed about the Enterprise Analytics solutions that are “Too Hot”, “Too Cold” and “Just Right.” Let's go with the assumption that our goal is to support the broadest possible audience in an organization.

Click here to read the remainder of the article: https://www.intricity.com/whitepapers/intricity-goldilocks-guide-to-enterprise-analytics

要查看或添加评论,请登录

Jared Hillam的更多文章

  • The Narrow Case for Data-to-Information Company Acquisitions

    The Narrow Case for Data-to-Information Company Acquisitions

    The rumors about Salesforce acquiring Informatica induced both a chuckle and a head shake. This isn’t a critique about…

    7 条评论
  • Salesforce Would Have Failed

    Salesforce Would Have Failed

    I started using Salesforce in 2004. The company I was with was piloting it, and they eventually became a Salesforce…

    8 条评论
  • Practical Automation for Code Modernization

    Practical Automation for Code Modernization

    Modernization Pressures In the last 4 years, the Data Management space has seen more modernization than the prior 20…

    2 条评论
  • Systems>Goals

    Systems>Goals

    In 2014 Scott Adams, the creator of Dilbert, introduced the "Systems>Goals" idea to me, and it has hovered around my…

  • WHY is this true?

    WHY is this true?

    The "Cheap, Fast, Good" paradox is something that people in the services space immediately relate to. For me, having…

    8 条评论
  • Data Lake VS Data Warehouse

    Data Lake VS Data Warehouse

    I was recently listening to a clinical psychologist talk about the different kinds of people that run organizations. He…

  • What I learned from Hurricane Harvey

    What I learned from Hurricane Harvey

    I've been wanting to write about this experience for a while, but just haven't had the words appropriately assembled in…

    3 条评论
  • What is a BI Metadata Layer

    What is a BI Metadata Layer

    If you’ve done any cooking, you’ve probably experienced what it's like to forget to add an ingredient or worse the…

    3 条评论
  • Growing Pains in Data

    Growing Pains in Data

    When you go home tonight, take a brief look at your house, and ask yourself. “How many stories or rooms could I add to…

  • Should you trust the cloud?

    Should you trust the cloud?

    We recently had a discussion with a financial services company which had several concerns about moving to the cloud…

社区洞察

其他会员也浏览了