Both DataWalk and Palantir Gotham are comprehensive products for integrating and analyzing silo’d data. Both can support “big data”, visual querying, robust link charts, histograms, 360-degree views of individual objects, and more. In addition, DataWalk offers the following:
Easily configurable: DataWalk utilizes a flexible ontology and is easily configured.
Easy integrations: DataWalk includes the App Center, a facility for writing scripts to integrate with new data sources, and to extend the functionality of the DataWalk application.
Algorithms are transparent: There are no “black box” calculations with DataWalk, so all results are transparent and easy to understand, evaluate, and audit.
Supports granular security: DataWalk’s platform ensures that each user only accesses the data they are authorized by the customer to see.
Rules and scores can be easily created and tuned.
End-to-end machine learning including integration with Jupyter Notebook as well as AutoML.
DataWalk product pricing is roughly 75% lower* cost than Palantir Gotham, and that’s only the beginning of the DataWalk cost advantage.
DataWalk enables you to minimize ongoing costs. No forward-deployed engineers are required, and DataWalk is sufficiently easy to use that you can add your own data sources and change the data model yourself, without necessarily requiring vendor assistance and professional services.
DataWalk costs are also highly predictable, so you don’t need to worry about unexpected big bills in the future.
DataWalk has been proven with customers worldwide, in both the public and private sectors. This includes customers who are replacing Palantir with DataWalk, such as the Money Laundering and Asset Recovery Section (MLARS) of the U.S. Department of Justice, which is generally considered to be the pre-eminent organization for anti-money laundering investigations. MLARS will use DataWalk to analyze large amounts of data associated with anti-money laundering investigations of financial institutions, money launderers, kleptocrats, and other criminal targets.
Customers who have reviewed DataWalk on Gartner Peer Insights have given DataWalk a perfect score of 5.0, while Palantir customers who have posted reviews on Gartner Peer Insights have given Palantir an average score of 3.6.**
Import any/all of your
data into DataWalk “as is”
Transform, normalize,
and fuse data
Organize data around business objects in a knowledge graph
No-code querying, graph analytics, and ML/AI
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** Using per-core pricing as posted for Palantir at https://www.gsaadvantage.gov/ref_text/GS35F0086U/0X04JP.3SQHIE_GS-35F-0086U_PALANTIRFSSPRICELIST.PDF, and for DataWalk at https://datawalk.com/wp-content/uploads/2018/08/RII-GSA.pd
* As of July 1, 2022.