Building Better Data Products with Data Observability

Modern organizations are looking for innovative ways to accelerate innovation, improve efficiency, and reduce risk in today’s competitive business landscape. As a result, data products—such as data-driven dashboards, visualizations, reports, models, and other processes that make it easier to leverage data—have become vital tools for companies of all sizes across virtually every industry.

Acceldata’s Founder & CEO, Rohit Choudhary, discussed data observability’s impact on data products during CDO TechVent, a virtual event for data leaders. Here’s a quick summary of Rohit’s key takeaways.

Roadblocks to Building More Data Products

Building new data products may be a top priority for many organizations, but the following roadblocks can delay or halt development:

Data sprawl: Web and mobile applications, IoT devices, and other business systems have made data more prevalent than ever. That’s a good thing, but managing the explosion of data isn’t easy—even for experienced data teams.

Tech sprawl: Increased demand for data has led to an equally complex data management landscape, which includes a seemingly endless list of vendors to support everything from data discovery to operationalization. Selecting the right data vendors and ensuring a seamless experience across an organization’s ecosystem can require considerable time and effort.

Talent shortage: Recruiting and retaining talented technical staff is challenging, especially in a tight labor market. With data teams stretched thin, just keeping the lights on can consume most of the data team’s attention. 

Bad data: An explosion of data paired with increasingly complex systems and staffing challenges is a recipe for disaster—one that frequently manifests itself in the form of bad data. Bad data erodes data trust and, ultimately, limits the impact of existing and future data products.

Overcoming issues like these instead of developing new data products isn’t just a missed opportunity. According to Rohit Choudhary, Founder & CEO at Acceldata, it’s far more strategic. “If you don’t have a good data product, then you won’t be a successful company in the future,” Choudhary said.

Data Observability to Support Data Product Creation

Clearly, there’s a lot of complexity for data teams to navigate. Continued reliance on outdated, manual processes is not a viable long-term strategy. “Data teams just don’t have enough visibility into what is going on in their systems, whether it’s their data infrastructure, the quality of data, or the business pipelines that were supposed to deliver data,” Choudhary said.

To keep pace with all of the data and related systems (without dramatically increasing headcount), a growing number of data teams are turning to data observability. “All of this complexity has to be simplified so data teams can focus on building what they do really well, which is building great data products,” Choudhary said. 

An effective data observability strategy accomplishes this by:

  • Making it easier to identify, resolve, and minimize performance issues
  • Providing spend intelligence to reduce the chance of cost overruns
  • Monitoring data reliability to improve data quality

Acceldata is a leading provider of enterprise data observability for enterprises across on-prem, cloud-native, and hybrid environments. Implementing the Data Observability Cloud from Acceldata can help increase reliability for existing data products and free up additional resources to build even more. 

For example, dashboards and alerts from Acceldata keep operators informed about potential issues so they can ensure SLAs are being met, prevent outages, and manage costs. Automated data quality monitoring and anomaly detection supports data reliability so practitioners and business users can trust the insights they gain from data products. 

Increase Confidence, Build Faster with Acceldata

Does your data team need greater visibility into its data and systems? Request a free trial of Acceldata’s Data Observability Cloud. Find out how it can help you build better data products in less time.

Photo by Michael Pointner on Unsplash