Webinar Review: How to Make Data More Consumable for Everyone in Your Organization

• Chris Chapman: Sr. Specialist Solution Architect at AWS Amazon Web Services, Chris Chapman works with customers to implement automation, security and governance best practices with native AWS Services and Partner products. As an AWS Certified Solutions Architect, he is skilled in cloud computing, data integration and architecture, SaaS computing, and software design and development. 

• Brian Prascsk: Advanced Analytics, Platform and Data Services at Wawa, Brian Prascak is a thought leader with over 15 years of experience in marketing analytics, product management, and data science functions. Before working at Wawa, he was involved with research and information services, financial services, payments, retail, consumer packaged goods, travel, and technology.

• Perry Stroll: Director of Engineering and Data Infrastructure at Facebook, Perry Stroll works with high-performance, large-scale data systems. Before working with Facebook, he was the Head of Data Technologies at Wayfair. He has extensive experience in software and product development, data infrastructures, and team development.

• Dave Mariani: Co-founder and Chief Technology Officer at AtScale, Dave Mariani previously held the position of VP of Engineering at Klout and at Yahoo! He was responsible for creating the world’s largest multi-dimensional cube for BI on Hadoop.

The Different Pieces of a Successful Data Project

The insightful seminar put on by these four speakers covers many areas, including the various pieces required for a successful data project. Many companies fail because instead of starting simple and building a more complex project as time goes on, they jump right to the latter. 

Innovation and insight is driven by access to data, time and computer to process it, and experts that can turn it into meaningful reports and graphs. This process is always unique for each company, but going even further, it is unique within each company’s internal structure. For example, each team or part of the organization can differ, and there are specialized tools and skills at each stage. 

Many companies struggle to fill each spot in each data science team with qualified experts, so it is crucial for them to democratize the advancements of one team, which will provide access for all teams to leverage it. 

One of the first things companies should do is offload heavy lifting from data science teams, and this can be done through things like automating infrastructure, providing self-service for common tools, enforcing compliance, and securing data with identity access management. 

When it comes to AWS specifically, data projects differ on key metrics, such as how much data, how fast it needs to be processed, and how the team manually manages the process. Some tools offer shortcuts for people with less expertise. 

With all of this said, gaining access to data is only a small piece of a larger challenge. Even with access to data, many companies struggle to gain access to the technical skills needed to put all of the pieces together. It is crucial for organizations to focus those with specialized skill sets on smaller parts in the flow, and they can bring them all together as the company standardizes on patterns with pre-defined pieces for data projects. The goal here is to efficiently enable business intelligence people with the right tools at the right time. 

If you want to learn more about how to make data and analytics consumable for everyone in your organization, you can register for the full seminar at AtScale.