Difficulty
In terms of corporate success and leadership, the value of data—its correctness, accessibility, and suitability—cannot be overstated. Obtaining as near to data as possible becomes even more important for a large-scale company. Our client came to us for that reason. Numerous internal users, incompatible technologies, and isolated data islands started to negatively impact the data analysis process as a whole, leading to erroneous conclusions, subpar business choices, and lost market possibilities. The challenge assigned to our team was to develop an AI-driven big data and self-service business intelligence platform that would enable hassle-free on-demand data access for the client’s over 3 million internal users.
We Committed To The Following Tasks:
To enable a 360-degree view of all data sources and data available in any format (Excel spreadsheets, invoices, PDFs, text files, databases, etc.) across the entire enterprise, create a user-friendly custom web gateway.
Provide business users with the ability to evaluate data and generate intricate ad hoc reports by developing a self-service business intelligence platform.
Establish a master data repository to act as the reference point for all data within the organization.
Connect petabytes of data from various systems to break down data silos and ensure consistency across data sources.
Replace, edit, or remove the soiled or coarse data records from the original data sources after identifying and fixing any incomplete, inaccurate, irrelevant, or wrong data.
Resolution
Utilizing graph data structures, a state-of-the-art technique that has shown to be extraordinarily effective at managing intricate networks of links and responding quickly to intricate and sophisticated questions
A particular dialect that is very similar to natural language and much easier to use than SQL, making search straightforward even for inexperienced people
Integration with the following important systems and data sources: Office365, Active Directory, SAP, Microsoft Exchange, Enterprise Data Lake, Slack, Zoom, Atlassian Stack (Confluence, Jira), etc.
The Report Builder functionality enables business users to query numerous data sources simultaneously to produce complicated reports that can be shared.
The ability of Hashtag Autocomplete to provide efficient search across a vast amount of data.
Hashtag Search is a function that helps users find the most relevant hashtags to make searching through search results easier.
An internal messaging feature that lets staff members transmit messages straight from the system to several channels of communication.
A straightforward API that makes it possible to create bespoke apps, integrate internal systems, and collect data even faster.
Role-based security in graph databases limits access to resources in the graph according to a user’s role, protecting sensitive data.
Effect
Three million internal users now have a comprehensive view of all previously unavailable data thanks to the self-service data analytics platform, which enables non-technical business users to filter, sort, analyze, and visualize data on their own.
In only a few clicks, business users may obtain actionable insights through multi-dimensional data presentation, which reveals previously hidden relationships for unrelated data. This allows them to base decisions on data rather than intuition.
Most routine reports are no longer created by data analytics teams.
Almost 3 PB of data are kept in the data lake, and the API processes 13 million queries and hundreds of millions of events daily.
Any internal application created using the API receives accurate and pertinent data.