IBM Analytics Engine vs. Jet Reports

• Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
• But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.

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Jet Reports is better suited if you have a specific population set you are looking at and less suited when querying or summing large pools or data, records, etc. I use a combination of Jet & SQL syntax when performing the latter because it allows me to harness the speed of our SQL server. Jet allows more for more customization when bodes better for users.

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• Jobs with Spark, Hadoop, or Hive queries are rapidly attained
• Can collect, organize and analyze your data accurately
• You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries.

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• Integrated reporting
• Customizable reports
• Easy to use

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• Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
• Bundling of the Cloud Object Storage should be included with the Analytics Engine.
• The inability to add your own Hadoop stack components has made some transfers a little more complex.

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• Tips and tricks
• Sharing best practices from other companies
• Online user forum

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Because it is not the costliest tool in this category but it serves the purpose. It is easy to use, cost effective, and works really well with the data stored on cloud. It has wide range of dashboard templates which go really well with different types of data sets. I would love to use it agains and again

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I hinestly have not used the support a lot but i have always had to way for longer durations to get a response on my emails. I have tried calling them a few times and the wait time was a little more than what i expected. They were able to answer my queries nonetheless

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We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.

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Jet Reports is light weight and has a minimal barrier to entry for new users. Tableau has a higher learning curve and is more cost prohibitive

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• This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
• IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
• The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.

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• Prediction analysis has helped the business to make future plans
• Report scheduling has eliminated a lot of manual work

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