A New Era in Data Science: Team-driven Predictive Analytics
How to optimize your data supply chain and data science resources

As data becomes more complex, so does the data and analytics industry. This space is fast-evolving, so solution providers need to quickly and confidently determine the best ways to solve pervasive customer problems. This is a challenge in and of itself.

Here at Datawatch, we are constantly enhancing our products to ensure our customers have access to the latest technologies to streamline their workflows and extract the best insights from their data. But we can’t so everything at once, so we often get asked by our loyal Monarch customers: “How do you decide what features and upgrades to include in your next release?”

The 3 Guiding Principles Behind Our Product Releases

Our product development efforts strive to address and balance our 3 core principles:

  • Delight our customers and satisfy end users by being responsive to their enhancement requests.
  • Improve our products to make complex data analytic work simpler.
  • Solve major challenges and current issues pervasive in the analytics industry.

Swarm Is Built on These Core Principles

We followed these principles in the latest release of Swarm, thanks to input from our loyal customers. Swarm’s new features also address issues faced by the analytics industry at large.

Most organizations are still learning best practices that allow them to leverage in-house data science resources effectively. But optimizing the data supply chain isn’t always easy, so organizations continue to struggle with understanding their customers, their business operations and their risks, through data.

A big piece of the puzzle is enabling better collaboration between data science teams and the lines of business, because understanding the context of a dataset is essential to developing trusted and accurate predictive models, which will ultimately drive enterprise-wide decision-making. A team-driven approach is necessary to help.

The latest release of Swarm helps streamline data science workflows to enhance enterprise-wide adoption of advanced analytics. Integration with Angoss, our predictive analytics platform, ensures that our customers can access the industry’s only enterprise data intelligence solution that enables all the data roles in an organization to leverage each other’s work and collaborate effectively.

By combining Angoss with Swarm’s data prep and data marketplace capabilities, data scientists can access a data supply chain workflow with centralized, curated, trusted datasets from across the organization in a single platform. They can now focus on developing a clear hindsight view of past performance, leveraging this context to create predictive models, and sharing the results with end users. This results in faster time to insight, trust in the analytical results, and unprecedented governance.

To learn how to reduce two of the most costly enterprise resources, data and effort, in your organization register now for our upcoming Data Science Central webinar led by Mike Ferguson of Intelligent Business Strategies Limited:

Optimize the Data Supply Chain

Date: Thursday, 1/31/2019

Time: 9:00 AM PST / 12:00 PM EST

Duration: 60 Minutes