Cloud

Becoming Data Driven: Make the Data Accessible, Integrated, and Reusable

Women Discussing Data

This is the third blog in a series that dives into how organizations become data-driven, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks. You can read the previous posts here and here.

A company becomes data-driven when they look to data to make important business decisions across the entire organization. There are several benefits to becoming data-driven including, but not limited to increased strategic agility, stronger customer visibility, streamlined operations, and having a more competitive edge. Manipulating and understanding data will allow an enterprise to make more informed decisions and may improve the customer experience.

 

The Data Catalog and Metadata Management

In the first blog, I explained the need for a data lake and making data accessible to knowledge workers, but when the data team starts loading the data lake with ever-increasing volumes and varieties of data how can the data be made accessible to knowledge workers across the organization? Successful data lake transformation and adoption of self-service rests in the ability of knowledge workers to find, access, use, and reuse data in the data lake. Ensuring success with enterprise data requires the formal integration of diverging lines of business, technology, and processes through data management and governance to create a comprehensive data catalog. A data catalog organizes the technical details around data assets, or metadata, into defined, meaningful, and searchable business assets to enable consistent understanding among all data knowledge workers. A data catalog is essential to knowledge workers as it combines and organizes details about data assets in the data lake by presenting them in an easy-to-understand format. The data catalog provides clarity into data definitions, synonyms, and essential business attributes so all knowledge workers understand and can leverage data as an asset. When knowledge workers have important data questions, they can turn to the data catalog, which identifies data owners, stewards, and subject matter experts, enabling easy collaboration between different organizational business units. A data catalog and metadata management will eliminate many of the pain points that now exist when knowledge workers try to gain business insight from data. The key pain points addressed are:

  • Improved productivity and reduced time spent by teams searching for relevant information or data
  • Increased visibility on key datasets that exist in the data lake
  • Avoid double purchases of similar datasets by different teams
  • Lineage to give knowledge workers a clear view of the flow and dependencies of data through the organization and business processes.
  • Improved collaboration between knowledge workers
  • Faster processes to access and interpret the data
  • Facilitated compliance with growing international privacy and reporting regulations
  • Common KPIs and Data Definitions make data comparable and understandable
  • Facilitated data relevancy and usage tracking

 

Google’s Data Catalog and Perficient’s Meta Data Manager

This Is The One Youre Looking ForI believe that Google Cloud Platform (GCP) is the absolute best data management platform available. Google Data Catalog, part of the GCP platform is a fully managed and highly scalable data discovery and metadata management service. Google Data Catalog helps knowledge workers understand data assets in Google Cloud and beyond. Integrations with BigQuery, Pub/Sub, Cloud Storage, and many connectors provide a unified view and tagging mechanism for technical and business metadata. Google Data Catalog empowers all knowledge workers in the organization to find or tag data with a powerful UI, built with the same search technology as Gmail, or via API access.

Perficient’s Metadata Manager is a framework that enhances the Google Data Catalog and offers a UI that makes metadata tagging and searching easier for knowledge workers and data stewards. Perficient Metadata Manager also provides data quality analysis and reporting capabilities.

 

 

Perficient’s Cloud Data Expertise

The world’s leading brands choose to partner with us because we are large enough to scale major cloud projects, yet nimble enough to provide focused expertise in specific areas of your business. Our cloud, data, and analytics teams can assist with your entire data and analytics lifecycle, from data strategy to implementation. We will help you make sense of your data and show you how to use it to solve complex business problems. We’ll assess your current data and analytics issues and develop a strategy to guide you to your long-term goals.

Download the guide, becoming a Data-Driven Organization With Google Cloud Platform, to learn more about Dr. Chuck’s GCP data strategy.

 

About the Author

Dr. Chuck is a Senior Data Strategist / Solution Architect. He is a technology leader and visionary in big data, data lakes, analytics, and data science. Over a career that spans more than 40 years, Dr. Chuck has developed many large data repositories based on advancing data technologies. Dr. Chuck has helped many companies become data-driven and develop comprehensive data strategies. The cloud is the modern ecosystem for data and data lakes. Dr. Chuck’s expertise lies in the Google Cloud Platform, Advanced Analytics, Big Data, SQL and NoSQL Databases, Cloud Data Management Engines, and Business Management Development technologies such as SQL, Python, Data Studio, Qlik, PowerBI, Talend, R, Data Robot, and more. The following sales enablement and data strategy results from 40 years of Dr. Chuck’s career in the data space. For more information or to engage Dr. Chuck in an engagement, contact him at chuck.brooks@perficient.com.

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