There has been an increase in the volume of data and data source types that can help an organization in its day-to-day operations as well as strategic goals. But with data comes the need for access and analytics at one’s fingertips.
Traditional data warehouses and business intelligence applications cannot efficiently handle this data. Retrieving the data for analysis can take long, making it irrelevant in this fast-paced world. Proprietary data warehouses also offer format limitations and scalability.
Data Lake Solutions
A data lake is an enterprise data hub that brings together data from separate sources. Its in-built big data and search engine solution makes it easy to search, enhancing the possibility of discovery, thereby facilitating better analytics, and reporting capabilities for end-users.
Indium Software’s Data Lakes services takes advantage of the inherent capabilities of the data lakes to design solutions that ensure:
- Data richness by storing structured and unstructured data from different sources and in varied format types, including XML, text, JSON, audio, image, video, etc.
- User productivity to access relevant data that aids in achieving corporate goals.
- Lower costs and scalability by using open source tools with zero licensing charges that allow scaling up as and when needed.
- Complementing existing data warehouses to work in conjunction for an integrated data strategy and protecting existing investments.
- Expandability such that it can be used for a variety of use cases for greater and deeper insights.
Indium Software’s solution architecture helps implement:
Real time Data Lake and Data Warehouse using NoSQL Databases
Modernize Data Warehouse with Big Data
Enables migration from traditional Databases to New Databases
Supports Cassandra, Hbase, MongoDb
Indium Software’s end-to-end planning and deployment services includes:
- Assessment of existing system infrastructure
- Recommendations for and guidance on platform and tools that can help implement the data lake architecture that best suits customer needs
- Implement security and governance strategy
- Pull siloed content into the data lake
- Prepare and enrich data and also extract meta-data, format conversion, augment, extract entity, cross-link, aggregate, de-normalize, and index
- Integrate front-end with a search and analytics user interface
- Test, manage services, and support to ensure peak performance