Before switching workloads to HDP, Luminar was ingesting 2 terabytes of new transactional data per month, from 300 raw sources. Now, Luminar appends new transactional data every day from 2,000 raw sources, which adds up to 15 terabytes per month. With Hadoop, Luminar increased the amount of data it captured by a factor of eight.
Luminar updates its data with constant ingest of new transactional data. Before Hadoop, it could take Luminar several days to ingest and join data to refresh one of their models. Now it takes only hours. This allows Luminar to tackle a greater number of projects and to process data for more clients in parallel. The company avoids an analytics bottleneck.
Luminar grew its business by delivering its data analytics services on a client-by-client basis where they gathered information in batch and then incorporated that into executive
presentations. The company is now building custom portals for select high-value clients. This will give those clients near real-time (and constantly updated) access to their most important data. Luminar sees this innovation as an important next step to scaling their business.