Yellowfin Launches Data Preparation Module for Analytics
Dec. 1 -- Global Business Intelligence (BI) and analytics software vendor, Yellowfin, has launched the first ever integrated and virtualized Data Preparation Module for analytics. Data preparation describes the process of transforming data into consistent formats suitable for exploration, analysis and report building.
Fully integrated into the metadata layer of Yellowfin’s BI platform, the new Data Preparation Module offers clients a unique method of integrating, managing and acting on more data in less time.
Yellowfin’s Data Preparation Module will enable organizations to easily model, profile, clean, shape, enrich, secure and publish all data desired for reporting and analytics in a single BI environment. The Data Preparation Module will be included as part of a standard Yellowfin license at no additional cost.
“With this release, Yellowfin has delivered another first for the BI and analytics software industry,” said Yellowfin Co-founder and CEO, Glen Rabie. “Yellowfin’s virtualized Data Preparation Module uniquely addresses the cost, complexity, security and inefficiency issues encountered by typical approaches to data preparation. No other vendor in the market is solving data preparation challenges in the same way as Yellowfin.
“Yellowfin’s Data Preparation Module truly supports the needs of data analysts, enterprise IT and business users. Data analysts can independently prepare data for analysis in less time, IT can easily govern that data, and business users have fast access to data they can trust in order to make critical business decisions.”
Yellowfin’s Data Preparation Module has been designed to overcome common challenges encountered when preparing data for analytics in three ways, by:
- Integrating data preparation processes directly into a single analytics environment
- Offering comprehensive data profiling capabilities
- Providing automated best practice metadata modeling functionality
A virtualized approach: Govern all data and analytical content in a single environment
Rabie said the problem with traditional data preparation was that it forced organizations to undertake data migration processes, which put data governance and security at risk.
“Moving data from one environment to another increases the risk of unauthorized data access,” said Rabie. “A virtualized approach means data analysts can directly connect to, prepare and analyze data sources in one place.
“Delivering virtualized data preparation will empower Yellowfin’s clients to maintain unparalleled governance, consistency and security across of all data and analytics content. Any data preparation actions performed will be uniformly reflected across all content – from reports and charts, to dashboards and Storyboards.”
Yellowfin Product Marketing Manager, Ivan Seow, said that by conducting data preparation and analytics in a single application, Yellowfin was also enabling organizations to avoid the cost and complexity of a multi-tool approach.
“Typical data preparation and analytics practices, conducted in separate software applications, introduce unnecessary data provisioning bottlenecks,” said Seow. “Then, there’s the expense of learning and maintaining two products – not to mention the propensity for standalone ‘self-service’ data preparation tools to create untrustworthy and unsecure islands of disparate data.
“Yellowfin avoids the chaos of traditional data preparation by delivering a single source of truth for all enterprise data. Go from data source to dashboard in one analytics platform and environment.”
Data profiling: Quickly introduce new analytics-ready data sources
Yellowfin’s data profiling capabilities enable data analysts to quickly assess the shape and quality of their data. The data profiling functionality visually displays the number and distribution of data profiled, providing statistics on the values within each column (such as minimum, maximum, median, average, empty and distinct values or outliers).
Seow said that Yellowfin’s data profiling features would enable data analysts to quickly confirm whether data being presented to users for analysis was complete, consistent and accurate.
“Yellowfin’s data profiling capabilities reduce the time taken to deliver new data for analysis to the business,” said Seow.
Best practice metadata modeling: Consistently deliver more insightful analysis
A key feature of Yellowfin’s data profiler is that it provides a list of Suggested Actions, which dynamically propose best practice metadata modeling solutions based on the profile results.
Types of transformations available via Yellowfin’s data profiling functionality include the ability to perform numeric and date grouping; apply filters, formatting, case statements and calculated fields; append, standardize or remove incomplete or inaccurate values; translate values held in the data source into business-friendly terminology (Organization Reference Codes); and assess a data set for attributes (such as zip or post code data) that would enable users to enrich data by adding a Yellowfin GeoPack. Yellowfin GeoPacks are pre-packed geospatial and demographic data points for specific countries or regions. GeoPacks can be downloaded from the Yellowfin Marketplace.
About Yellowfin
Yellowfin is a global Business Intelligence (BI) and analytics software vendor passionate about making BI easy. Founded in 2003 in response to the complexity and costs associated with implementing and using traditional BI tools, Yellowfin is a highly intuitive 100 percent Web-based reporting and analytics solution. Yellowfin is a leader in Mobile BI, Collaborative BI and Embedded BI, as well as Location Intelligence and data visualization.
Source: Yellowfin
