ANALYTICS, DATA, INTELLIGENCE, AND A.I.
Analytics
As computing power grows and data accumulates from diverse sources like mobile, IoT, and internet devices, analytics becomes vital. It includes information, data, and database services, offering insights for informed decisions amid the expanding landscape of data solutions and concerns.
Artificial Intelligence
While big data started for internet based click stream data analysis, it has quickly made its way to become an integral part of all BI and analytic solutions. Companies with big and small data are leveraging the power of Hadoop and No SQL to build data lakes and replacing traditional staging layers with big data. Cost savings compare to traditional systems is incredibly lower.
With the power of AI, Machine Learning, and Big Data, statistical analysis and forecasting are becoming very affordable.
Traditional statistical tools such as SAS have 2 problems: they sample partial data, and they cost millions to implement. Big Data based statistical tools can be free and they can analyze full datasets without the need to sample the data.
NoSQL data stores allow streaming data to be ingested, analyzed and reacted in ways that were never possible before.
Graph databases allow real-time impact and ripple effect analysis. If a logistics chain breaks due to a component/vehicle failure, the alternatives can be calculated in real time and optimal reconfiguration could be implemented.
Database
For terabytes and petabytes, precision in design is key. Our databases, tailored for efficiency, swiftly respond to queries in seconds. With Relational and Columnar VLDB for OLTP and DW, we ensure seamless, high-performance data processing.
We have designed databases storing petabytes of data capable of responding to queries in sub-seconds.
Intelligence
Many clients create Fact and Dimension tables without understanding efficient dimensional modeling, affecting performance at large volumes. While theories form a basis for logical models, each database demands a unique design for optimal query response. OLAP and Business Intelligence (BI) techniques, like Dimensional Star/Snowflake models, add sophistication, recognizing that relational or columnar databases vary in design needs is crucial for tailored solutions.