IBM Analytics Engine vs. Minitab Statistical Software

• 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.

Incentivized

Minitab Statistical Software is used from development batches to commercial batches to identify that process is in state of control through various charts and graphs. we can optimised our process by continuous monitoring of product trends. its is less suited where large number of data need to handle and evaluate..

Incentivized

• 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.

Incentivized

• Life cycle product verification and control
• Cpk value calculation and control
• Historical data evaluation and decision making based on that data.

Incentivized

• 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.

Incentivized

• This to be make financially affordable
• Direct feeding of data provision need to provided
• It must be update to handle large data.

Incentivized

I would give 10 out of 10 rating due to its functionality and easy to use interface. Its included wide range of tools like graph, chart, time study graph. There is predefined inbuilt templet available for easy to use and understand process well. there is availability of vast training materials enhances our experience.

Incentivized

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.

Incentivized

• 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.

Incentivized

• We could control our process and its continuous monitoring that reduce process failure chances.
• It helpful in database decision making process like rejection or acceptance of batch.
• Process is improved and productivity increased.

Incentivized