Self service analytics are touted as the holy grail to performance management. In reality, self-service analytics are merely self-service selection and formatting of graphs and charts. Self-service analytics is not achievable without integrating the data management, compute and visualization layer. The expectation of self-service analytics leads to costs increasing every time there is even a small change in the data model or computation logic.
Data models need to be re-done each time data changes in the source systems. Simple things as new columns or change in column names can cause the analytics platform to break-down and lead to increased cost of maintenance and managed service.
With RevolutioBI’s front-end no-code data mappers, any change in data structure will not impede the output. With dynamic tables in RevolutioBI, changing table structures and relationships can be done with a few clicks. Without RevolutioBI, change in source system data, naming conventions and scheduled processes can significantly escalate cost of maintenance.
Compute scripts in today’s chaotic and archaic data analytics frameworks are written all over the place. This includes database queries, ETL queries, data pipelines, queries using specific functions, querying external compute engines and additional queries at the visualization layer. All these compute scripts are difficult to trace, costly to maintain and in many cases only understood by the person who originally wrote them.
With RevolutioBI’s no-code Computation Studio, all queries and computation scripts across the data journey are written in a single place without writing a single line of code. Each output at each step of the query is displayed on screen and traceable preventing your analytics platform becoming a black-box.
Most data analytics projects focus on data aggregation, cleansing and visualization. The most important elements of compute, data movement and data management on an ongoing basis are ignored. Each of these aspects are then retrofitted into the framework with heavy dependence on proprietary technologies and cloud services. Each new addition adds a significant new unbudgeted cost.
RevolutioBI is pre-architected to cover virtually every data transmission and management scenario and an onboard optimized compute layer that requires no external engines.
Traditional wisdom tells you that a data analytics project needs a data lake, data streaming tech, ETL tech, computation engines, analytics platforms, data miners, data cleansers, master data management tools, visualization layer and a content distribution server. All these components and at times many others are procured separately from different providers all of which stacks up one hidden cost source after another.
RevolutioBI has no hidden costs – pre-architected to cover the entire data journey.
Data analytics projects, generally clubbed with data warehousing endeavors, tend to be multi-year budgetary blackholes. The end result to show for these tend to be static reports. With each passing day and person-hour incurred, the cost of the projects keeps piling up. Many a times, post completion or go-live costs of people managing these projects tends to be larger than the original budget for deployment.