Geckoboard vs. IBM Analytics Engine

Great value for the money. Excellent for smaller agencies with multiple projects and teams in a smaller space. We can quickly roll out mobile displays to help with a particular deployment push or monitoring a clients website engagement. It's also useful for showing live data without requiring analytics to run reports from a CRM, etc.

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• 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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• User self-help - the video tutorials and a robust publicly accessible knowledgebase.
• Geckoboard can aggregate data from a number of other apps into a singular dashboard.
• Sleek, dark UI.

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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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• A bit more flexibility in the number of columns would be nice.
• Ability to scale to mobile device (web).
• App capabilities are missing on Android.

• 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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My company did not renew due to changes in the organization.

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With a simple interface and available templates, creating basic dashboards is easy. Obviously depending on the data you want to visualize, there may be higher learning curves. That being said, they have a huge amount of integrations and extensible frameworks. If you are using anything made in the past ten years there is an API function or integration that can get it talking to the platform. As such, it's pretty easy to hit the main data points you want and get it on a cheap display in front of your team.

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The support levels vary based on the level of plan that you have but that's to be expected. Virtually everything except the Enterprise plan has basic chat/email support. While they are responsive they are not going to be much assistance in helping you figure out API calls or implementing 3rd party integrations. That is to be expected and the support community can pretty much get you in the right direction if you look.

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Domo is more robust. We do use both because Geckoboard is really easy to show the rest of our team without the need for additional licenses.

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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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• While we originally used this as an internal IS tool, we eventually have expanded it to be used by nearly every department.
• Because pricing is monthly, we can grow or decrease our usage based on our current client needs.
• Because it is low cost and easy to deploy, we can utilize it in place of considerable resources in analytics and reporting by delivering snapshots of data without pulling reports.

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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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