Rapid Deployment Data Analysis Platform
- Dramatically accelerates time to value by quickly blending multiple data silos, providing first answers in days, instead of many months
- Accelerates understanding by enabling instant creation and testing of ad-hoc hypotheses via an intuitive visual interface
- Dramatically increases analytical capabilities of business analysts
- Enables you to change the data structure in the analytics system on the fly
- Easily scales to many billions of records
Blend Data In Days, Even If No Common Key!
With traditional systems it may be impractical to develop a target workspace for complex data blending, but DataWalk eliminates this issue. After loading data you can easily iterate on the logical data structure as your needs evolve, and you can easily add/integrate additional data sources at any time, on-the fly. With DataWalk, customers have accelerated the process of creating a data structure by up to 100X. See an example of a three-day POC.
Do Complex Queries Without SQL Or Programming
With DataWalk, there is no need to write software, create data marts, or write SQL queries. Business analysts and data scientists can do complex queries of the entire unified data set via the DataWalk Universe Viewer, which is an intuitive visual interface. Coupled with flexible structuring, these capabilities enable a vastly simplified process for data preparation and analysis, dramatically reducing time to value.
Trusted Results, Even If Data Is Dirty!
Traditional tools often cannot operate on dirty data, requiring long, expensive data cleanup projects. DataWalk is different! With DataWalk you can quickly do basic profiling of your data, extract unique records from duplicates, do minor transformations on the fly, and if desired, simply exclude dirty data objects from your analysis.
Get Control of Shadow IT
With DataWalk you can maintain a centralized, governed analytics environment, while still enabling authorized users to add their own private data for their individual use. As an administrator, you will now have visibility and control of such users and data.
ETL Once; Get A Browse-able Workspace Ready For Analysis
You only need to ETL data once into DataWalk, where data can be cached or stored. You then have a single browse-able workspace that’s ready for analysis. This is in contrast to traditional solutions, which may require that data is ETL’d multiple times as data is moved around for various analyses.
Query, Graph, Flows, And Search – All Without Data Movement
DataWalk provides a single integrated workspace for various types of analyses, including visual querying, network graph, flows analysis, histograms, and searching/traversing the entire data set. Unlike other systems which may require data movement for such analyses, with DataWalk all are done within our single workspace, without requiring further data movement, and can easily scale to handle many billions of records. This reduces infrastructure costs and further accelerates time to results.
Define And Test Hypotheses At The Speed Of Thought
With DataWalk you can instantly, iteratively define and test hypotheses via an intuitive visual interface. In traditional approaches hypothesis testing is a time-consuming process as each hypothesis must first be carefully defined. With DataWalk you can easily, instantly create and test a hypothesis via the Universe Viewer. And, as the Universe Viewer is an intuitive visual tool, business analysts can now easily define and test hypotheses as well. With DataWalk you can test new hypotheses as quickly as you think of them.
Subset Your Data And Encode For Machine Learning
Want to do further analysis using R or Machine Learning? If so, then DataWalk makes it easy to identify appropriate data samples to train and test your models.
An Open Analytic Environment
With RESTful access and JDBC/ODBC support, data can be made available to many other tools, such as Tableau for further visualization, or R for statistical analysis.
Great For Silo’d Data That Comes From Mergers & Acquisitions
DataWalk provides powerful new capabilities for any organization that is struggling to derive value from data spread across multiple silos. Organizations who are struggling to bring together and analyze data from new silos that came along with mergers or acquisitions are a particularly strong fit.