Have you been wondering when you should considering building a full cloud data stack? Here at Data Clymer we work with companies that understand the potential for data to drive growth and revenue, but they can’t get insights in a timely manner necessary for their fast-moving businesses. The underlying cause is either that 1) the company doesn’t yet have a data stack or 2) they have hacked one together that is far from optimal.
Companies that don’t have a data stack are amazed what they can do once they have one. A 360 degree view of the customer is in their reach for the first time, and they can create dashboards customized precisely for their business. For example, The Latest Scoop (a lifestyle and fashion retailer) leveraged Data Clymer to build their first cloud data stack using Looker and Panoply. The retailer now has a game-changing system that brings near real-time data to manage store inventory throughout the day (they had 24 hour batch data prior), and combines store traffic with sales data to track a new corporate metric: traffic conversion.
Other companies fall into the classic trap of assuming that any software engineer can build a data stack. However, they quickly realize that data engineering is an entirely separate skill set lacking inside the organization. That’s where Data Clymer comes in. We are experts and have done this many times before, and we’ll play the role of the entire data team. Tact.ai, an artificial intelligence solution for Salesforce, is a great example. Data Clymer replaced their old on-premise, slow data system with a fast, reliable cloud data stack integrating Looker, Matillion, Amazon Redshift, and Segment. Tact.ai’s application engineers no longer work nights and weekends to keep up with data job failures or manually pulling ad-hoc data. Their new system runs smoothly and has been adopted across the entire organization.