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DataSteroid

Revolutionizing Data Integration: Unifying Disparate Data Sources for Actionable KPIs

Overview

TechVariable was approached by an HR tech giant looking to facilitate extracting customizable user-defined data from multiple data sources. Their clients used various off-the-shelf applications for different business functions, creating disparate, unconnected data, hindering meaningful, organization-wide Key Performance Indicators (KPIs) creation, and complicating Business Intelligence (BI) operations.

Challenges

  • Data Disparity: The client's customers used numerous disconnected applications for diverse business functions. This disparity obstructed the generation of comprehensive, organization-wide KPIs.
  • Hindrance to BI Operations: The difficulty in curating data from disparate sources posed significant challenges to efficient BI operations.

Solutions

  • Development of Connector Engine: We utilized DataSteroid’s connector engine to extract customizable user-defined data from any data source. This connector engine supports OData sources, including Microsoft Azure, SharePoint, Office 365, Salesforce, and Tableau, as well as non-OData sources like JIRA, REST, and SOAP APIs.
  • Streamlined Data Extraction and Analysis: DataSteroid fetches details of available data based on the application chosen by the user. The user then selects the necessary data types for analysis. Subsequently, the connector injects the data into the BI pipeline to extract valuable insights through KPIs.

Result

Introducing the new connector engine empowers customers to seamlessly extract data from diverse and disjointed sources, paving the way for generating meaningful and holistic insights and KPIs. The process is further streamlined through the automation of data fetching, achieved by implementing schedulers, and the seamless integration of data into business intelligence (BI) systems. This automation enhances the efficiency of the KPI generation process and ensures a more cohesive and insightful analysis of the consolidated data.

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