Analytics, Information, Data and Database services
As computing power increases and data from external sources, mobile, sensor and internet devices continue to accumulate; new data solutions and concerns will continue to increase.
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 incredible lower.
With the power of big data and machine learning, the 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 are 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 logistics chain breaks due to a component/vehicle failure, the alternatives can be calculated in real time and optimal reconfiguration could be implemented.
Relational and Columnar VLDB for OLTP and Data Warehousing
Terabytes and Petabytes of data require proper design. We have designed databases storing petabytes of data responding query in sub second. We design databases for business needs query needs not per white papers that give generic design principals.
OLAP and Business Intelligence (BI) (Dimensional Star/Snowflake)
We see many clients building Fact and Dimension tables without proper understanding of dimensional modeling that will perform at large volumes. Theories and principals are a great start for logical models but each database requires different design for same query. Not every relational database or columnar database should be designed the same way.