This insight was the duo’s impetus to develop ROKITT ASTRA product, which automatically discovers ‘hidden’ and undocumented data elements in structured data, traces their relationships and how information flows across an entire enterprise. Using proven scalable technologies, ROKITT automates this process thus removing process inefficiencies and creating a reliable way for organization to discover and maintain its data blueprint.
ROKITT ASTRA uses machine learning algorithms to discover the implied and often unknown data relationships that are not contained in a company’s metadata. Data changes, moves and grows making it difficult for enterprises to keep metadata up to date. Discovering data relationships within a database and across databases is very time consuming for enterprises. ROKITT ASTRA was designed to address both data growth and data management challenges that data intensive companies have been plagued with for decades. “Companies can now quickly and cost-effectively improve their understanding of their data assets across their businesses, often consisting of undocumented legacy or siloed systems,” says Oksana.
ROKITT ASTRA is a self-learning system that continually improves its performance, including accepting input from SMEs within a company. It has the capability to recognize implied dependencies between values in a database. For example, one column in a table can reference data in different columns in another table.
With more complete information, companies can make better decisions that have greater impact on the bottom line. Additionally, “we see ROKITT ASTRA being used across SDLC—business analysts, architects and testers can utilize ROKITT ASTRA to plan and execute complex technology projects,” notes Oksana. Customers look to use ROKITT ASTRA as part of impact analysis. “Customers migrating onto the cloud or going through re-platforming efforts can leverage ROKITT ASTRA to assure proper impact analysis is completed prior to migration, to identify redundant data, to identify data dependencies and to identify operational/transactional data. Customers who are moving to data lakes or are trying to understand what is in their lake can leverage ROKITT ASTRA to figure out data relationships automatically.”
Companies can now quickly and cost-effectively improve their understanding of their data assets across their businesses, often consisting of undocumented legacy systems