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.
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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.
- 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.
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.
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.
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 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.
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.
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.
IBM Analytics Engine is a Hadoop and Spark service allowing users to rapidly build and deploy analytics applications.
Frequently Asked Questions
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.
The most common users of IBM Analytics Engine are from Enterprises and the Information Technology & Services industry.