A host of new, valuable features have been added to the Acceldata Data Observability platform so you can ensure your team is working with reliable data and managing your data operations cost-effectively.
But before we get to the details, I think it’s important to have some perspective on WHY we’re developing these innovative new features. Every product wants to be faster, smarter…or just better in some way. And while we know that our platform is providing something no other vendor can, we’re doing it because there are specific needs in the market, and we take great care to address them.
We spend every day learning about the needs of data leaders and helping them solve the issues that prevent them from maximizing the value they get from their enterprise data. The Acceldata Data Observability platform delivers insights from the four essential elements that address data health:
- Data assets
- Data pipelines
- Data infrastructure
- Data users
As data is now the single most essential piece of intellectual property for every enterprise, the need to effectively manage that data has become mandatory. Data leaders are prioritizing data observability and Gartner emphasized its’ broad appeal and utilitarian need at the recently concluded 2023 Gartner Data and Analytics Summit.
Our platform ingests all relevant information from these elements and orchestrates them to deliver critical insights and outcomes for the three most important use cases that are top of mind for every data leader:
The sections below summarize the new features and capabilities grouped by the three use cases, along with links to more detailed documentation.
The new features listed in the table above provide a comprehensive and holistic view of your data reliability across all your data assets. Armed with that information, teams can scale their reliability through the application of rules and policies across similar data assets.
You can see how the Acceldata Data Observability platform provides holistic insights into data reliability via the new KPI monitoring dashboard:
With more data sets and workloads operating in the cloud, cost control is at the top of the priority list for data executives. The concept of spend intelligence is about having an always-on dashboard of intelligence of your data platform spend and costs over different dimensions. This changes the economics of your data environment because detailed analysis enables teams to perform chargeback of data platform costs to various business entities and users within your organization.
Additionally, data teams take back the function of budgeting by eliminating cost overruns and being able to use recommended configurations to rightsize data platform resources according to cost.
- Cost/spend granularity
- Chargeback granularity
- Stock monitors
An example of a cost dashboard for Snowflake is shown here:
Ultimately, data teams are responsible for maintaining constant vigilance of data platform performance to ensure data is delivered in a timely manner. That’s a huge burden and one that cannot be performed manually, which is why data teams look to our platform to help them get granular insights into queries and resource use to identify execution problems and performance bottlenecks. They can eliminate improper or unneeded resource use with guardrails and apply Acceldata’s recommended configurations to optimize data platform resources according to performance needs.
- Recommendations dashboard
- Platform-specific recommendations
- Query Studio & monitoring
- Compute & infrastructure alerts
You can see this in more detail in Acceldata’s Query Studio, here:
Request a personalized demo from our team today to see for yourself how Acceldata is leading the way for data reliability, spend intelligence, and operational intelligence for data observability.