Data-driven transformation leveraging multi-source data engineering
Organizations are inundated with data already and the volume is growing by the minute. To gain maximum value from their data assets, companies must build data pipelines to help transform and transfer the data into a format that is ready for use for data scientists and other end-users. Growing data volumes offer enormous potential for organizations to generate business value from captured data, offer exceptional customer service and help stay ahead of the curve in today’s competitive global market.
Our data engineering services help make data more useful and accessible to all data consumers. We help our clients gather data requirements, maintain metadata about data, ensure security and data governance, and process data according to their unique requirements.
Indium uses a tailored approach to help firms monetize and optimise the value of their data. We establish a solid data foundation and use data mining to generate insights. Our objectives are to address major obstacles that restrict firms from scaling and transforming themselves into data-savvy rivals.
Design and develop data pipeline (ETL and ELT)
Design and develop data products with APIs
Enable data quality management
Indium provides the complete range of data engineering solutions that help optimize analytics, data warehousing and data science programs of companies across industries such as manufacturing, BFSI, education, retail, technology and more.
Indium has helped its clients establish successful data engineering initiatives based on the following factors:
An international banking and financial services firm came to us for a storage house to accumulate vast amounts of data, as the database currently being used was cost prohibitive and a huge hassle to maintain and manage. Consequently, the client decided to move all the data from their local database to the cloud, while limiting direct access to the database.
By using Striim, real-time data integration and data streaming was processed, in which a huge amount of data was migrated from Oracle database on-prem to a Postgres database on Google Cloud Platform. The architecture was implemented by enabling customized visualization, and effective data monitoring. To overcome the access restrictions on the Oracle database Striim Agent was leveraged, which acted as a third party for streaming the data. Additionally, instant alerts were created to notify when there were multiple streams of data being processed in the pipeline.
Usage of Striim reduced the time consumption for transferring the data from the Oracle on-prem database to the Google Cloud Platform by 90%. The complications in setting up the data replication process was reduced by 87%. Striim ejected a 95% increase in security while accessing the data from database.
Gartner defines embedded analytics as a digital workplace capability that allows users with data analysis…