The Complex Analytics Landscape
Having spent much time in the data management world, I like to talk quite a bit about how the data landscape has changed with data sources growing at an alarming rate in different places: on-premises, cloud and SaaS. But the growth and dispersed nature of analytic information is not just relegated to data. Add other analytic siloes to the mix and the landscape complexity grows exponentially. Let’s take a deeper look at the analytic landscape and the impact on analytic professionals.
Organizations have compiled a wealth of information that analysts can use to answer new questions from management, and it is not just data. Analytic information can come in the form of:
- Reports and analyses in BI systems
- Reports and analyses in specialized service provider systems
- Reports in SaaS applications
- Models in data science tools or notebooks
And this analytic information and knowledge is spread across numerous locations:
- The number of data siloes is large and growing. A recent survey by the Neebo team revealed that 84% of analysts need access to 11 or more data sources for their analytics.
- The 2019 SaaS Trends Report by Blissfully reported that organizations larger than 1,000 employees average using 203 SaaS solutions.
- Many organizations use multiple BI, data discovery and reporting tools and there are many disconnected BI/reporting siloes even if using the same toolset.
- Documents can be on local drives, cloud objects stores, cloud document stores such as Box or Google Drive, or content management systems such as SharePoint or Confluence.
Analytic teams are under tremendous pressure to deliver more results in much faster timeframes than ever before. Management is constantly examining and re-examining the state of the business and markets, asking new questions daily. And the answers they want are far more sophisticated, as consumers and global business operations are ever more intricate, and sales and marketing gets more segmented and localized.
No longer is it acceptable to wait weeks or even days to get answers – management wants detailed actionable data rapidly to make course adjustments on a dime. According to a leading BI vendor, it still takes 4.8 days to produce a report answering new questions.
All of the aforementioned analytic assets can aid analysts and data scientists in performing new analyses and answering a question the same day management poses it. Perhaps:
- Individual assets answer part of the question and when combined deliver the full result,
- There are untapped data assets that can answer the question, or
- A report, analysis or dataset that answers the question is already out there
But with such a disparate landscape for the analytic assets, the analysts and data scientists may not know the assets exist, have access to the right assets, or understand and trust that the assets can be used to answer their question.
The Neebo Virtual Analytics Hub provides a single access point where analysts and data scientists can collaborate on analytic assets of any kind to accelerate their analytic cycles and deliver faster, more insightful answers to digital age questions. With Neebo, analytic professionals and knowledge workers can:
- Search and discover new analytic assets regardless of location, system and type
- Consume and combine the assets to deliver faster more detailed answers
- Collaborate and share knowledge on assets to build greater trust
Best of all, Neebo enhances your existing environment and does not replace it. It provides a single plane of glass to all your analytic assets, working with your existing BI and data science tools, data sources, catalogs, SaaS applications and services, and document stores to increase the visibility into these assets, futher their use, build trust and accelerate analytic cycles.