{"id":26410,"date":"2022-12-29T02:47:53","date_gmt":"2022-12-29T02:47:53","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/29\/scaling-simplified-accessible-data-analytical-tools-with-machine-learning-and-artificial-intelligence-capabilities\/"},"modified":"2022-12-29T02:47:53","modified_gmt":"2022-12-29T02:47:53","slug":"scaling-simplified-accessible-data-analytical-tools-with-machine-learning-and-artificial-intelligence-capabilities","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/29\/scaling-simplified-accessible-data-analytical-tools-with-machine-learning-and-artificial-intelligence-capabilities\/","title":{"rendered":"Scaling simplified, accessible data analytical tools with machine learning and artificial intelligence capabilities"},"content":{"rendered":"

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With digital transformations occurring across businesses everywhere, data is accumulating en masse. But this data is useless without the proper analytical tools, which have grown too complex and expensive for enterprises managing multicloud architectures. Sisense Inc. looks to address the cloud chaos with artificial intelligence-powered capabilities at an accessible price point, scalable through its availability in the Amazon Web Services Marketplace.<\/p>\n

\u201cWe\u2019re taking the bricks out of the briefcase.\u00a0We\u2019re assembling it into something that users\u00a0can deploy for their use cases,\u201d said Scott Castle<\/a> (pictured), chief strategy officer at Sisense.\u00a0\u201cFor us, AWS is perfect\u00a0because they focus on the hard bits\u00a0of the underlying technologies,\u00a0we assemble those to make them usable for customers,\u00a0and we get the distribution.\u201d<\/p>\n

Castle spoke with theCUBE industry analysts John Furrier<\/a> and Savannah Peterson<\/a> at AWS re:Invent<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed Sisense\u2019s relationship with AWS, how analytical tools have changed over tech generations, and the company\u2019s approach to making its platform accessible. (* Disclosure below.)<\/em><\/p>\n

Future of analytics<\/h3>\n

Sisense, Castle explained, is giving its users the building blocks they need to craft their own products to suit their needs. With Sisense, users have access to AI-boosted capabilities, with machine learning already built-in, with what the company calls \u201cinfused analytics.\u201d<\/p>\n

\u201cThe idea is you break this up\u00a0into very small digestible pieces.\u00a0You put those pieces into user experiences\u00a0where they\u2019re relevant and when you need them,\u201d Castle said.<\/p>\n

One of Sisense\u2019s defining selling points is its ease of use for software developers. Users can input data points into algorithms with minimal coding, as Sisense does the heavy lifting.<\/p>\n

\u201cWith Sisense,\u00a0because our bread and butter has always been embedding, it\u2019s all architected to be API-first,\u201d Castle explained of the company\u2019s use of application programming interfacing.\u00a0\u201cIt\u2019s integrated for software developers with graphical user interfaces (GUI)\u00a0but it also has all those low-code and no-code capabilities\u00a0for business users to do the Minority Report-style thing, and it assembles endless components\u00a0into a workable, digital workspace application.\u201d<\/p>\n

Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of AWS re:Invent<\/a>:<\/p>\n