

The intensifying competition in the analytics world is driving many startups to seek additional funding or, if that’s not feasible, a buyout. One of the most recent examples is Hadoop hosting provider Altiscale Inc., which was last week revealed to be in process of finalizing a $125-million-plus acquisition agreement with SAP SA.
The deal is set to provide a hefty return for its investors while giving the German software giant a big competitive boost in the analytics market. SAP could offer Altiscale’s Hadoop service alongside the managed version of its relational HANA store to let customers process both their structured and unstructured data without having to use third party software. It might even end up integrating the two offerings so that data can be moved back and forth during different stages of the analytics lifecycle. Such functionality could go a long way towards winning over large organizations with complex business intelligence use cases that involve multiple types of information.
Large enterprises with complex analytics requirements are also the target market of SigOpt Inc., a data science startup that raised $6.6 million last week from a group of investors led by Andreessen Horowitz. The capital will be used to widen the adoption of its namesake platform, which employs a technique called Bayesian optimization to fine-tune the behavior of various business applications. It can be used for everything from speeding up scientific simulations to improving the accuracy and performance of artificial intelligence software, an area where Facebook Inc. is active as well.
The social networking giant last week open-sourced a trio of machine vision tools designed to ease the creation of image analysis applications. According to Facebook researcher Piotr Dollar, the suite makes it possible to only to identify what a picture depicts in general terms but also parse distinguishes specific details such as what kind of objects are being shown and how they interact. The technology has the potential to dramatically reduce the amount of time and effort that organizations need to invest into extracting meaning from their media content.
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