IBM Analytics Engine Reviews and Ratings

Use Cases and Deployment Scope

We use [IBM Analytics] to provision, manage, run and retire Apache Hadoop and Apache Spark clusters. With its calculation engine, this enterprise performance

management solution helps the users move beyond the limits of

spreadsheets, automating the planning process to drive faster, more

accurate results. We use it to unify data sources into one single

repository, because it enables users to build sophisticated, multidimensional

models that drive forecasts. So far we haven't had any problems with the software.

Likelihood to Recommend

We are at present utilizing IBM Analytics Engine and it works incredible. Following are the things that I like the most about this product is:-

- Simple to Utilize

- Reasonable Cost

- With only a couple seconds you can ready to fabricate and convey groups

- you can without much of a stretch break down information through different applications

Use Cases and Deployment Scope

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.

Likelihood to Recommend

IBM Analytics is more suited to an environment where there is big data or a large volume of data coming in from different sources. For those who are already on IBM Cloud Engine, they can leverage the maximum out of IBM Analytics Engine. Systems with Hadoop & Spark applications should go with this tool.

Use Cases and Deployment Scope

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.

Likelihood to Recommend

IBM Analytics Engine works well for managing and running multiple clusters, keeping them organized and monitoring your budget better by separating out the computer costs from the storage costs. It’s only a good option if you are already working within IBM Cloud, if you are an Azure or AWS shop, you have better options within those subscriptions for both price and performance. Also, if you don’t have much in Hadoop or Spark clusters, the features this tool offers only add incremental value to how you were managing it before.

Use Cases and Deployment Scope

As far as I know, we are the only department in our rather large organization that is currently using the IBM Analytics Engine. We needed a relatively low-cost solution to perform analysis without a huge amount of maintenance or upkeep required. It also allowed us to perform tasks we did not foresee, such as analyze data across multiple applications.

Likelihood to Recommend

The IBM Analytics Engine is particularly well-suited for situations in which you are required to analyze data from a myriad of sources. The drill-down capabilities make this a very powerful tool, but the implementation of large-scale projects requires watching the tutorials first, in our opinion. It is nice that they offer a free trial version so that you can test limited features first.

Use Cases and Deployment Scope

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.

Likelihood to Recommend

I think the IBM Analytics Engine is well suited for large corporations looking to increase their analytics game. This is truly an Enterprise product that can capture data across multiple workflows to help a business grab a hold of what's going on with their data. I don't feel that the IBM Analytics Engine is well-suited for smaller companies. The complexity is just to large to roll-out to a company that might not need all the power of this product.

Use Cases and Deployment Scope

We used IBM Analytics Engine for one of the public sector clients who have to deal with massive amounts of data coming from their mobile app and centralized internet web applications. They were previously running a custom solution developed by one of the big fours and were unfortunate enough to have lost a data due to infrastructure failure. The high-level idea was to separate computing and storage and simpler administration of clusters without losing the analytics capabilities.

Likelihood to Recommend

If you are looking for a relatively cost-effective solution of running extremely powerful analytics without the headache of complex administration and maintenance it generally comes with, IBM Analytics Engine is a worthy option to be considered. It helped our clients cut down the maintenance and administration and had an added advantage reducing data integrity and downtime issue by separation of two fundamental aspects of any web application

Use Cases and Deployment Scope

It was used by my department only. It helped to analyze our program outcome throughout the 6 months that I was working with that program. It was really helpful, and shortened our analysis procedure by a lot. Moreover, it saved the company a lot of labor and time.

Likelihood to Recommend

It is pretty good for my work, but it might not be useful for all programmers, even in my company. Also users needs to understand it pretty well before using it. Instructions for how to use it is probably helpful for users who have never used it or heard about it.

Use Cases and Deployment Scope

<ul><li>We used it for a research project to implement big data analysis on a YELP dataset from 2017 to answer a sales related question. We used the default Ambari file browser to upload the data, Hadoop ecosystem for data cleaning, Hive to query the dataset followed by TABLEAU for visualization.</li></ul>

Likelihood to Recommend

<ul><li>Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.</li><li>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.</li></ul>

Use Cases and Deployment Scope

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.

Likelihood to Recommend

In my case, it’s very nice to be able to use the service for education at an affordable price.