Having a comprehensive BI intelligence platform provides complete visibility and control of the data flow, and enables company-wide consistency across the entire BI environment.
TEL AVIV, Israel (PRWEB) May 07, 2020
Octopai, a leader in metadata management automation for BI & Analytics, announces today that a recent survey conducted with Dataversity reveals that 86% of business technology professionals are frustrated with their current metadata management tools and the amount of time they spend on manual data mapping to deliver results to the business.. The majority (66%) of respondents stated that it takes them days and weeks to find the source of an error in a report and to conduct impact analysis ahead of making a change to a field in their data environment.
Octopai partnered with Dataversity in early 2020 and surveyed over 250 business technology professionals across 20-plus industries in the roles of data information/data governance, data and/or information architecture and business intelligence and analytics. The survey focused on the critical role of automation in dramatically improving metadata management daily operations for BI & Analytics, specifically around data lineage, data discovery and business glossary.
The survey results show that BI groups in organizations are finding it nearly impossible to keep up with the massive amounts of data they are dealing with on a daily basis, and welcome automated metadata management tools to help them find and understand their data in order to deliver results to the business more quickly and more accurately.
One of the main challenges for data teams that arose in the survey was implementation of a business glossary to create company-wide consistency of data assets, reports and dashboards. It has been described by Gartner as “the semantic foundation for logical data warehouses and business analytics,” yet despite the clear need for a business glossary, implementation can be so time consuming and tedious that most organizations end up either putting it off completely or getting stuck somewhere along the way. The survey results emphasize the need for a comprehensive solution that comprises automated data lineage, automated data discovery and automated business glossary capabilities to enable BI & Analytics teams to gain full visibility and control of their data.
“With so many highly frustrated data professionals out there, it is not surprising that so many have already sought out and are actively seeking automated tools to dramatically reduce time spent on daily BI operations and manual data mapping,” said Amnon Drori, CEO of Octopai. “Having a comprehensive BI intelligence platform provides complete visibility and control of the data flow, and enables company-wide consistency across the entire BI environment.”
Additional survey findings demonstrate the top issues that business intelligence teams face, which include:
The most challenging use cases ranked by respondents:
68% said implementation of business glossary
64% said daily data operations (business inaccuracies, business changes, etc.)
45% said implementing a data dictionary
36% said system migration/upgrades
32% find that regulatory compliance is a hardship
83% said automation of metadata management for key functions like data lineage and data discovery is important to their team’s success
Octopai’s cloud-based automated BI intelligence platform has become a necessity for organizations - especially now during the Coronavirus outbreak as it enables BI & Analytics teams to continue to deliver quickly and accurately, and to adapt to the ever changing environment and needs of the business, even while working remotely .
Octopai was founded in 2015 by experienced BI professionals who had a need for time-saving and simplifying solutions. Octopai's SaaS platform automates metadata management and analysis, enabling enterprise BI groups to quickly, easily and accurately find and understand their data. Octopai is empowering BI with complete data lineage, discovery and automated business glossary capabilities for superior BI operations, data governance, and data quality. The company was recognized as a Gartner Cool Vendor for Data Science and Machine Learning in 2018 and their investors include North First Ventures, Gefen Capital and iAngels.