AtScale’s seminar on “How to Make Data More Consumable for Everyone in Your Organization” provides valuable insight into how leaders can centralize data and move it away from silos, making it more accessible to everyone in an organization .
The seminar includes four speakers:
- Chris Chapman: Principal Specialized Solutions 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 proficient 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. Prior to working at Wawa, he was involved in research and information services, financial services, payments, retail, consumer goods, travel and technology.
- Perry walk: Director of Engineering and Data Infrastructure at Facebook, Perry Stroll works with high-performance, large-scale data systems. Prior to working with Facebook, he was Data Technology Manager at Wayfair. He has extensive experience in software and product development, data infrastructure and team development.
- Dave Mariani: Co-founder and CTO at AtScale, Dave Mariani previously served as VP of Engineering at Klout and Yahoo! He was responsible for building the world’s largest multidimensional cube for BI on Hadoop.
The different parts of a successful data project
The insightful seminar hosted by these four speakers covers many areas, including the different elements required for a successful data project. Many businesses fail because instead of just starting out and building a more complex project over time, they jump right into it.
Innovation and insight are driven by access to data, the time and computer to process it, and the experts who can turn it into meaningful reports and graphs. This process is always unique for each company, but to go even further, it is unique within the internal structure of each company. For example, every team or part of the organization may be different, and there are specialized tools and skills at every step.
Many companies struggle to fill every position in every data science team with qualified experts, so it is crucial for them to democratize a team’s advancements, which will allow all teams to benefit from them.
One of the first things businesses should do is offload the heavy lifting from data science teams, and this can be done through things like infrastructure automation, providing self-service. for common tools, compliance enforcement and data security with identity access management.
When it comes to AWS in particular, data projects differ on key metrics, such as how much data, how quickly it needs to be processed, and how the team manually manages the process. Some tools offer shortcuts for less experienced people.
That said, accessing data is only a small part of a larger challenge. Even with access to data, many companies struggle to access the technical skills needed to put all the parts together. It’s crucial for organizations to focus specialist skills on the smaller parts of the flow, and they can bring them all together as the business standardizes models with pre-built elements for data projects. The objective here is to efficiently enable people in charge of business intelligence to have the right tools at the right time.
If you would like to learn more about how to make data and analytics usable by everyone in your organization, you can register for the full seminar at At scale.