Conga Grid vs. Dataiku

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.

Incentivized

I would recommend it because it's an amazing tool for different levels of users. From Business Analysts to Data Scientists to Managers, various employees can make use of this tool to make data-driven decisions. I'm not sure about where it would be less appropriate as I'm using it as Data Scientist and so far it pretty much caters to my need.

Incentivized

• Allows recruiters to service candidates within a radius of a desired city/location
• Allows recruiters to see multiple fields/information on multiple candidates at once
• Allows for easier ranking/sorting by salary, years of experience, etc

Incentivized

• Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
• Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
• Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
• Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
• Support from research till final MaaS solution deployment.

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• Sometimes Conga goes slower when using it at a high volume
• Being able to pull more data through LinkedIn and Indeed
• Job match function

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• Its community support is very limited at the moment
• Complex to integrate with automation tools such as Blue Prism

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It could be easier to create views or there could be additional training with step by step examples in conga community

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As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.

Incentivized

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.

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

Incentivized

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.

Incentivized

Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.

Incentivized

• It has benefited us positively, as I stated earlier- it allows us to filter down results of 65,000+ candidates to a search of 1-100 candidates.

Incentivized

• Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
• Platform also ease tracking of data processing workflow, unlike Excel.
• Build-in data visualizations covers many use cases with minimal customization; time saver.

Incentivized