Hashboard (discontinued) vs. IBM Analytics Engine

Glean.io is exceptionally well for creating automation data visualisation dashboards. Exploring the data is again highly effective. Visualisations are easily customisable to best suit the requirements of the team. Collaborating and commenting around the dashboards is very smooth. If there are any changes in the system or any feature requests, the support team takes some time to respond

Incentivized

• 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

• Workflow is easy and clear due to clean and state of the art interface
• Model creation is easy
• Possibility for custom SQL code for database connection is very helpful

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

• Querying has to be done by users only. There can be ways to automate querying using templates
• Not able to clearly check the query run time
• The customer support team can be little more proactive while communicating any changes and resolving any queries

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

For simple use cases, Glean.io is a lightweight alternative to SAP Analytics Cloud. Provisioning, testing, and documentation are easier and less intimidating in the Glean.io case. Thus, it is easy to explore without firing up the sales machinery of the big corporates. Thus, the process of looking into and testing it out was way more convenient. Further, the data ops features were new to use and seem to be unique with Glean.io.

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

• Optimised the DB management team by 30%
• Reduce in data visualisation dashboards TAT by 50%
• Increase in revenues and savings by 20%

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