Conga Grid is a productivity tool within Salesforce that allows users to view, sort, and manage data batches from a single screen. It helps users to find and manage the information and insights needed with fewer clicks and less screen switching. Conga Grid helps its users to save time, improve data quality, get a clear view into needed data, and create a more productive workplace in Salesforce to drive growth across the organization. …
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IBM Analytics Engine
Score 7.1 out of 10
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IBM BigInsights is an analytics and data visualization tool leveraging hadoop.
If a user has to perform a specific update over many records, don't use a List view... use Grid. It allows users to quickly track their work, set additional formatting preferences and avoid constantly tracking work outside of Salesforce which leads data discrepencies and errors.
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
In general, Conga is a strong company with a depth of talent in its support team. However, when new releases occur, the changes can be somewhat jarring to users as the interface does not offer the ability to hide or show messages related to the changes - all users get the same messaging from Conga around changes to their tool.
CongaGrid is native to Salesforce and takes advantage of the Salesforce Lightning experience to provide a strong, full-featured solution for cross-object data access and manipulation. The upgrades are seamless, occurring without requiring administrator application of the changes. Embedding Excel-like functionality directly within Salesforce opens up a host of use cases for accessing and manipulating Salesforce data.
I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service whether I use it or not
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.