Did You Know?

1

Quickly fuse data from many disparate sources into a single unified view for easy search and analysis.

Graph technology and a Knowledge Graph makes it possible

2

Re-organize your data around relevant entities – things like people, transactions, phones, or anything else – in an intuitive visual model.

DataWalk provides an ideal knowledge graph.

3

Quickly process and analyze vast amounts of complex data.

Though DataWalk provides compelling visualizations, we hold 10+ patents for data processing and analysis.

4

Use DataWalk as an intelligence database as well as an analytical system.

Easily expand capacity of your intelligence database simply by adding additional nodes to a DataWalk cluster.

5

Automatically identify clusters of interest, such as clusters that may be indicative of organized crime groups.

Define the cluster pattern you are looking for, and DataWalk will find that pattern anywhere in your data.

6

Analyze data via no-code visual queries, graph analysis, and ML/AI.

DataWalk unifies key analytical techniques for use in analyzing vast amounts of data.

7

DataWalk includes a robust link analysis facility.

Instantly add connected objects using all your data.

8

Create machine learning models in Jupyter Notebook.

You can run Jupyter Notebook within DataWalk.

9

Quickly create and execute complex no-code queries traversing many data sets.

DataWalk has unique technology for ensuring complex queries can complete, and complete quickly.

10

Get a 360-view of any object of interest.

Even available for casual users on mobile devices who simply want to search the DataWalk database.

11

Easily modify the data structure on-the-fly, without interrupting system operations and without impacting downstream systems.

This is enabled by DataWalk’s flexible logical data model, which is another of our foundation technologies.

12

Efficiently import and analyze data from Palantir Gotham.

Other vendors worked on this problem for years and could not do this. DataWalk is an attractive Palantir Gotham alternative.

13

Easily extend DataWalk functionality via plug-in Apps.

Apps are plug-in programs which can be written by DataWalk, our partners, customers, or the open source community.

14

Take advantage of a hybrid graph/relational database that gives you the best of both worlds.

Graph technology is all about the connections and relationships in the data, while relational databases are ideal for processing tabular data.

15

Analyze text, including automatic extract extraction.

With DataWalk text analytics you can process PDFs, MS-Word documents, and other text files.

16

Perform entity resolution for vast amounts of data.

Identify possible matching records using advanced fuzzy matching algorithms and various other techniques for entity resolution.

17

Quickly find all shortest paths between data objects, across vast amounts of data.

DataWalk has unique technology for executing graph algorithms at scale.

18

Take advantage of full ML Ops pipelines.

Create, run, and tune your ML models using real data.

19

Deploy a system optimized for The Enterprise.

DataWalk supports automatic application of change request artifacts, DevOps automation, online backups, SSO, and optional high availability configurations.

20

Automatically analyze images and video.

These capabilities are enabled by DataWalk Apps, which can leverage your internal infrastructure or external services to derive information from images and video.

21

Easily do hypothesis testing.

When finding an answer (e.g., building a visual query), you can instantly go back to a previous step to change a parameter or try a different path, instead of starting all over.

22

Easily visualize flows of vast amounts of data, including money, calls, materials, or anything else.

Unique DataWalk technology enables flows analysis on large-scale data.

23

Easily create and modify no-code scores.

Via a simple visual interface.

24

Deploy DataWalk on-premise, in the cloud, or in a hybrid configuration.

Supported cloud environments include AWS and Microsoft Azure.

25

Utilize Explainable AI to understand your analysis.

Use DataWalk xAI, scorecards, and “breadcrumbs” (visualizing query logic) to build trust in results.

26

Quickly make new internal and external data sources operational and actionable.

Configure hassle-free integrations with DataWalk’s Universal Connector.

27

Easily configure alerts yourself for proactive notification and/or to trigger advanced workflows.

Get automatic notification upon any desired change in your data.

28

Collaborate

Easily share queries, link charts, investigation folders, or anything else with colleagues who have appropriate permissions

29

Do time and location-based matching across vast amounts of data.

For example, analyze millions of license plate reads to find two cars that were in close proximity, if desired in the same timeframe.