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.
IBM Analytics Engine is being used by my organization to analyze our data across multiple applications. We use it primarily to gather data to be used to analyze application performance and reliability. This data allows us to ensure that we are delivering the best possible application performance to our customers and business partners across all channels.
- We are able to build and deploy clusters within minutes to simplify user experience and increase scalability and reliability.
- We are able to scale and compute on-demand to handle newer workloads like machine learning.
- We really like that we are able to access and administer the application via multiple interfaces.
- Some of the documentation can be overwhelming and very technical. We would love to have some documentation written for non-technical people.
- We would like to see better communication from IBM regarding upgrades and patching cycles of the product.
- The learning curve for this product is steep. This is definitely not a product that will be used right out of the box.
- 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.
We did an evaluation of Google Analytics and Microsoft Azure Stream Analytics in comparison to the IBM Analytics Engine product. We choose the product offering from IBM because we felt that for our company, this product offered a more complete and comprehensive package to satisfy our data analytics needs. We also appreciated that this product is coming from IBM, and we have a long-standing partnership with them and they have provided us with many valuable products and services over the years.
January 26, 2018
Great product
I go to California state university, Los Angles for a master in information systems. Our computer science department uses IBM Analytics Engine along with the students to give them hands on experience with a real time tool. It works pretty great. I used IBM Analytics Engine to learn about Hadoop and soon will learn about Spark SQL and so on.
- Compact clusters. Via the trial versions that I use, I have a great insight of how different organizations create clusters and manage data
- Fast: the load time at registration is a bit slow. But after creating the first cluster, everything went way faster
- Realistic: hands on experience
- Reasonable cost
- Lagging at some point. Inconsistency in maintaining and running clusters.
- Should allow the cluster to last longer before refreshing
- It’s a bit confusing to navigate through the site. Sometime I thought I hit the right section then it lead me to another one.
- The log in page is inconsistent. I could find 3 different IBM log in page via Google. And then have to click many things that will lead to where I want.
- Increasing learning success. My class and I were able to practice real tools
- The only downsize is without the school, it would be unaffordable to use the tools
Our professor has worked with IBM And many major tech companies. He’d recommend us which tools to use. And comparing to Azure, IBM is more convenient to use.