User friendly platform that allows you to easily analyze your Data Analytics
We use [IBM Analytics] to provision, manage, run and retire Apache Hadoop and Apache Spark clusters. With its calculation engine, this …
Overview
What is IBM Analytics Engine?
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.
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Product Demos
2 IBM Analytics Engine View Instance Details
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3 IBM Analytics Engine - Enabling logging using - "platform logs" Log Analysis Instance
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Product Details
- About
- Tech Details
What is IBM Analytics Engine?
IBM Analytics Engine is a Hadoop and Spark service allowing users to rapidly build and deploy analytics applications.
IBM Analytics Engine Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
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(39)Reviews
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January 14, 2021
IBM Analytics - A Must Try Analytics Tool
We have recently started utilizing IBM Analytics & so far it has been a good experience. Our Data Intelligence team along with the DevOps team makes use of this tool as they deal with an enormous amount of data on a daily basis. The majority use it analyze the overall performance of all the applications related to Hadoop by gauging the datasets & check for any inconsistency in their behavior.
- Easy-to-use User interface with featured pack functionalities.
- Scalable & customizable according to user needs.
- Powerful yet simple cluster administration.
- Affordable Pricing.
- Could improve upon step-by-step instructions & make it more comprehensive.
- Can be more prompt with their customer service.
- Could come up with an e learning module for using the tool.
- Saved considerable amount of time dealing with clustering & its administration.
- Seamless & faster processing time helped us increasing ROI in return.
- Decreases the need of relying on multiple tools for data analytics.
Our data analytics team happened to try IBM Analytics just to get acquainted with it & it turned out that this tool fits our business requirement better than the one which we were using in terms of the features along with the level of support that they provide. so, choosing the tools was a no brainer given IBM's stellar reputation.
We have just begun to explore very large data sets and gave the IBM Analytics Engine a test to see how it would work for us. We were quite surprised at how complete and easy it was to set up and manage multiple Spark and Hadoop clusters. The separation of computing and storage really drives the performance up and gives you a better architecture with which to manage your overall big data plans.
- It’s easy to integrate if you are already on IBM cloud, and even if you are not you can still explore the whole package with their free Lite plan and some service credits they offer.
- Unlimited clusters without any performance degradation is a nice selling point. The smaller cluster size seems to work since it is only the computer, and not mixed with storage.
- The connection to Watson Studio helps manage your jobs as you submit them to the cluster, and this is a nice easy relationship with Analytics Engine.
- 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.
- It has saved us quite a bit of time managing our catalog of clusters and keeping things organized.
- Since we had a division we acquired running IBM Cloud, it was easy to get it running and try it out, but we found we prefer our Azure configuration better simply to keep our technology in alignment across corporate functions.
- I definitely see some cost savings by separating out the storage and compute. It helps you start to put an appropriate price tag on certain instances of big data.
- Azure HDInsight, AWS Cloud9, Snowflake and Oracle Advanced Analytics
IBM Analytics is a great tool and a welcome addition to your overall IBM strategy. I think in cases of tools like this, you either go with what your platform works best with or you go completely different with a 3rd party, like Snowflake. We are an Azure shop and just happened to have a division on IBM and wanted to give it a try. Performance-wise it stacks up against the other platform-specific tools, so you should feel comfortable when your data strategy tips in favor of needing more organization.