Anomalo Pulse dashboard aims for data quality insights
The startup is enhancing its platform by providing users with a new dashboard that brings visibility into the state of data used for data analytics and business intelligence.
Data quality startup Anomalo expanded the capabilities of its flagship platform today with the general availability of its new Pulse dashboard for data insights.
Anomalo, based in Palo Alto, Calif., was founded in 2018 and raised $33 million in a series A round of funding in 2021. The vendor's platform provides data quality visibility for data pipelines that are used for data analytics and business intelligence.
With the Pulse dashboard, Anomalo is now providing its users with an enterprise-wide view of data across an organization. The dashboard can identify data trends about timeliness and quality that can then be used to optimize data usage.
The enterprise challenge for data quality is fundamentally that data comes into the business faster than it can be cleansed and governed, and that data quality is treated as a static one-time exercise rather than an ongoing process of cleansing and enrichment.
Hyoun ParkAnalyst, Amalgam Insights
"The enterprise challenge for data quality is fundamentally that data comes into the business faster than it can be cleansed and governed, and that data quality is treated as a static one-time exercise rather than an ongoing process of cleansing and enrichment," said Hyoun Park, an analyst at Amalgam Insights.
"This approach makes it difficult to effectively prioritize data quality efforts across the organizational data ecosystem," he said.
Pulse provides a new view for data quality
The market for data quality is growing, and it is competitive, with multiple vendors vying for customers, including Bigeye, data integration vendor Talend and Superconductive.
Meanwhile, Park said the data quality charts provided by Anomalo aren't necessarily unique in and of themselves. He noted that modern data quality technologies commonly provide visualizations for data quality coverage, completeness and improvements. But what differentiates Anomalo to some degree is its iterative and continuous approach to measuring data quality and validation over time.
"In addition, Anomalo Pulse provides directional guidance on the most important data quality activities at any given moment, rather than an undifferentiated and nonprioritized list of data quality issues," Park said.
"These charts help demonstrate Anomalo's focus on helping data departments to see the full scope of data quality challenges that data analysts face across the business's data environment," he added.
An organizational view of data quality
Since its start, Anomalo has provided users with a view into data quality. Elliot Shmukler, co-founder and CEO of Anomalo, said what's new with the Pulse dashboard is that it provides an organization-wide, broad view into data quality.
Before the Pulse dashboard, Anomalo's platform provided data quality information on specific data sets and tables that an organization decided it wanted to monitor.
"Now, you can go to the Pulse dashboard, and you can get a summary of all the tables that are being monitored in your organization," Shmukler said.
Anomalo's Pulse dashboard provides data quality metrics and trend information on data across an organization.
The dashboard view also brings visibility into the adoption of data quality practices across an organization by showing what data an enterprise actually monitors and uses.
The Pulse dashboard provides what Shmukler referred to as a traffic light color-coding system of red, yellow and green for each metric the dashboard displays for data quality. He noted that a high-quality table doesn't generate alerts for errors and consistently meets service-level agreements for timely delivery of information, while a low-quality table is the opposite.
"When you pull up the dashboard, you can immediately see which are the red things that you should focus on and the green things where you're doing well," he said.
