GREENPLUM CHORUS - Collaborate and Derive Insight from your Data
Agile Analytics for Data Science Teams
Search, explore, visualize, and derive insight from data across your enterprise with real-time collaboration to increase productivity of the global data science team to deliver analytics agility
Integrated development environment that expands insights with simple access to third-party data and analytics tools to promote a rich analytics ecosystem
Freedom to Open Source
Lower the barrier of entry and reduce vendor dependencies for the data science collaboration platform
Big Data Agility for your Data Science Team
Greenplum Chorus enables Big Data agility for your data science team. The first solution of its kind, Greenplum Chorus provides an analytic productivity platform that enables the team to search, explore, visualize, and import data from anywhere in the organization. It provides rich social network features that revolve around datasets, insights, methods, and workflows, allowing data analysts, data scientists, IT staff, DBAs, executives, and other stakeholders to participate and collaborate on Big Data. Customers deploy Chorus to create a self-service agile analytic infrastructure; teams can create workspaces on the fly with self-service provisioning, and then instantly start creating and sharing insights.
Chorus breaks down the walls between all of the individuals involved in the data science team and empowers everyone who works with your data to more easily collaborate and derive insight from that data.
Greenplum Chorus breaks down the silos across the enterprise by replacing the backlog of email with a single interface for all your organization’s data, together with virtual databases for exploration and innovation, and social collaboration for insight and analysis. Greenplum Chorus provides rich social network features that revolve around datasets, insights, and other key Chorus components — allowing Big Data Analytics stakeholders to all participate and collaborate in the same environment. The result is that the data science team can collaboratively discover, share, and discuss insights that have a meaningful impact to the business.
Gone are the days of hunting through email or shared drives for one specific comment or piece of code. Instead, everything is tracked and available through the Greenplum Chorus interface. Chorus delivers federated search across data assets anywhere in the enterprise. Chorus indexes all metadata, comments, SQL, and data assets to create a living data dictionary available in the form of a search prompt.
With Chorus, analysts can browse and explore database and hadoop datasets across the enterprise. Once imported into the workspace, Chorus will manage the flow of data, and will track the dependency and update their copy when the source is updated with new data. Analysts can operate on the data, and can share the results of their analysis as a new dataset that can be discovered and accessed by other analysts.
Workspaces and Sandboxes
With Chorus, the data science team can create new analytics workspaces and sandboxes with a few simple clicks. There is no longer a need to file a ticket with IT and wait hours or weeks for the solution. With self-service provisioning, users can instantiate new sandbox schemas on the fly within existing Greenplum Database instances.
Greenplum Chorus creates and maintains an active repository of analytics artifacts, which allows for easy file sharing, versioning, change tracking, and archiving. This content sharing infrastructure preserves the value of its files regardless of organizational changes.
Additionally, by providing the data science team a rapid visual representation of information, there is no longer a need to export the data to a local desktop, import into R or another tool, and then create a visualization. Not intended to replace advanced reporting tools from our BI partners, Chorus includes a set of visualization options that provide a data preview to speed insight and understanding of data. Chorus supports histograms, frequency, heat-map, time series and box plot charts for on-demand visualizations.
Greenplum Chorus provides a single interface with rich social network features that facilitate participation and collaboration amongst Big Data Analytics stakeholders. As a result, the entire data science team can bring their datasets to the table and collaboratively discover, share, and discuss insights that have a meaningful impact on the business. For example, the Create Insight feature makes it easy to publish an insight across Chorus. An analyst can share any insight directly with team members, who can then make comments, brainstorm about overlooked possibilities, and generate new questions of their own. By delivering fast, efficient project workspace environments and enabling freedom of exploration for the entire team, Greenplum Chorus lets organizations achieve greater business insight and economic value from their data than ever before.
Open Source Through the Openchorus Project
Through the OpenChorus Project (www.openchorus.org), Greenplum provides a framework for fostering the collaborative data science community, including individual developers, application partners, data source providers, data scientists, and the Chorus user community. Greenplum Chorus becomes the collaborative data science platform that helps to expand data science insights with simple access to third-party data and data science tools. Greenplum lowers the barrier of entry to data science collaboration technologies through the OpenChorus Project, an effort to open source Greenplum Chorus. The OpenChorus Project also reduces the dependency on Greenplum or any software vendor to desired features and to the ease and flexibility of customization based on the needs of each organization.
Big Data is not “easy” Life is made harder when work product can walk out the door with each new hire and fire. Greenplum, a division of EMC, has tried to address this with a number of innovative initiatives. First, it has made Chorus, a collaborative data science platform open-sourced. Next, it has formed a number of partnerships with other participants in the Big Data ecosystem to make the data scientist’s life and productivity vastly improved. In this Neuraspective™, Neuralytix examines the impact of this progression on the Big Data “ecology”.
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