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Latest Videos

Webinar: Unlocking the Value of Cloud Data and Analytics

From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data.

Demo: Unravel Data - Tuning Data App Performance Automatically

Optimizing data apps shouldn’t be trial and error. This takes nights and weekends away from DataOps teams - and it’s incredibly inefficient. Unravel provides an “expert in a box” feature, driven by AI, that provides DataOps teams with tangible insights and recommendations to optimize data apps. Need to fix a bottleneck to meet an SLA? Trying to improve the overall efficiency of data pipelines? Unravel makes this easy with specific, automated recommendations (all the way down to the code-level) to tune your data apps for better performance.

Demo: Unravel Data - Optimizing Cloud Costs at the Cluster Level

Most DataOps teams have a huge opportunity when it comes to optimizing their cloud costs. Today, the standard for success of many developers is ensuring that their jobs are running at all costs. The efficiency of those jobs isn’t the top priority. With Unravel, DataOps teams can optimize cloud costs by rightsizing their clusters. Unravel makes it easy to identify clusters that are consuming a large percentage of resources, and drill down to see automatic recommendations to improve the efficiency of those clusters.

Demo: Unravel Data - Map Your Workloads to the Cloud (and Calculate Costs)

When a data team is migrating applications to the cloud, they’ll need to anticipate how many resources those apps will consume. This can often take a DataOps teams into unfamiliar territory since on-prem applications are assessed very differently from a utilization standpoint. This information is critical to inform the cloud architecture - and to anticipate the total cost of ownership for the cloud migration.

Unravel: DataOps Observability Designed for Data Teams

Today every company is a data company. And even with all the great new data systems and technologies, it’s people—data teams—who unlock the power of data to drive business value. But today’s data teams are getting bogged down. They’re struggling to keep pace with the increased volume, velocity, variety, complexity—and cost—of the modern data stack. That’s where Unravel DataOps observability comes in. Designed specifically for data teams, Unravel gives you the observability, AI, and automation to help you understand, optimize and govern your data estate—for performance, cost, and quality.

Demo: Unravel Data - Preparing for Cloud Migration with Automated Cluster Discovery

One of the first steps of any cloud migration is creating an inventory of the applications and services that are currently being used. Today, that involves a lot of manual interviews with people from across the business to understand the needs behind each cluster. This process, as you can imagine, is incredibly prone to errors and miscommunications that can negatively impact migration planning efforts.

Demo: Unravel Data - How to Avoid Tuning & Replatforming Delays

How can your DataOps team anticipate bottlenecks that might occur during a cloud migration? One of the most common issues is version incompatibilities. On prem environments tend to run older instances of applications (vs. newer cloud environments) - which means that your team will need to consider any incompatible code before migrating.