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The 22 most important data technologies ranked

31/03/2016 by Pascal CALOC


Forrester has taken 22 of the most important big data technologies to task, finding that the majority have reached a state of deployment in the market.

In its new Big Data Tech Radar report, the following big data technologies were assessed: 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.

Forrester claims that only a single technology has reached the 'equilibrium phase' – MPP data warehouse – i.e. it's best placed to overcome firms' end-to-end data management analytics hurdles over the next few years.

The research firm's advice to enterprise architects was to make the most of their thirst for end-to-end solutions, using it as a barometer for implementing technologies in the survival and early growth phases.

The enormous and unpredictable changes in the big data technology landscape are the product of the sheer number of technologies in the survival phases, the report suggests. Enterprise architects would be wise to utilise their technology innovation lab to examine each technology, allowing them to offer some value when asked to help with a point solution need.

Practitioners should look to technologies in the growth phase to help solve business problems that arise when exasperated line-of-business executives are finally prepared to admit to issues with integrating across the customer life cycle.

Meanwhile, the solitary equilibrium phase technology and the late growth phase technologies are best suited to highly demanding, end-to-end data management analytics challenges. Once a firm is well set to connect customer experiences across the life cycle, these technologies must be the go-to, the report concludes.


Big Data & Analytics

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