In a new Big Data Tech Radar report, Forrester identified and evaluated 22 of the most important big data technologies.

These include MPP data warehouse, predictive analytics, data virtualization, distributed file store, stream analytics, search and knowledge discovery, data quality, data governance, SQL-for-Hadoop, insight platforms, data preparation, NoSQL database, in-memory data fabric, data integration, data encryption and masking, monitoring and administration, data science tools, stream ingestion, data modelling and metadata management, big data-as-a-service, machine learning libraries, and artificial intelligence.

Only one technology made it to the equilibrium phase -- MPP data warehouse -- meaning that it’s ranked highest to meet businesses’ end-to-end data management analytics challenges in the years to come.

Forrester says enterprise architects should use their businesses appetite for end-to-end solutions as a barometer for introducing technologies in the survival and early growth phases.

First, the number of technologies in the survival phase is fueling enormous and unpredictable changes in the big data technology landscape. Use your technology innovation lab to examine each of these and to prepare to respond when your business says, “Can you help us with this point solution need?”

Second, technologies in the growth phase exhibit mature vendor ecosystems with enough innovation and hungry market entrants to keep vendors sharp. Look to these technologies to help solve business problems that crop up when impatient line-of-business executives finally admit to problems with integrating across the customer life cycle.

Third, late growth phase technologies and the one equilibrium phase technology are ready for most demanding, end-to-end data management analytics challenges. When one’s firm is ready to connect customer experience across the life cycle, these technologies must be the standards.

Telecomasia.net