Data democratization allows everyone in an organization to have access to the data they need, and the necessary tools needed to use this data effectively. In short, data democratization enables better business decisions.
In this episode, Rama Ryali, a Senior IT and Data Executive, chats with Kris Jenkins about the importance of data democratization in modern systems.
Rama explains that tech has unprecedented control over data and ignores basic business needs. Tech’s influence has largely gone unchecked and has led to a disconnect that often forces businesses to hire outside vendors for help turning their data into information they can use. In his role at RightData, Rama worked closely with Marketing, Sales, Customers, and Leadership to develop a no-code unified data platform that is accessible to everyone and fosters data democratization.
So what is data democracy anyway? Rama explains that data democratization is the process of making data more accessible and open to a wider audience in a unified, no-code UI. It involves making sure that data is available to people who need it, regardless of their technical expertise or background. This enables businesses to make data-driven decisions faster and reduces the costs associated with acquiring, processing, and storing information. In addition, by allowing more people access to data, organizations can better collaborate and access tools that allow them to gain valuable insights into their operations and gain a competitive edge in the marketplace.
In a perfect world, complicated tools supported by SQL, Excel, etc., with static views of data, will be replaced by a UI that anyone can use to analyze real-time streaming data. Kris coined a phase, “data socialization,” which describes the way that these types of tools can enable human connections across all areas of the organization, not just tech.
Rama acknowledges that Excel, SQL, and other dev-heavy platforms will never go away, but the future of data democracy will allow businesses to unlock the maximum value of data through an iterative, democratic process where people talk about what the data is, what matters to other people, and how to transmit it in a way that makes sense.
EPISODE LINKS
Apache Kafka 3.5 - Kafka Core, Connect, Streams, & Client Updates
A Special Announcement from Streaming Audio
How to use Data Contracts for Long-Term Schema Management
How to use Python with Apache Kafka
Next-Gen Data Modeling, Integrity, and Governance with YODA
Migrate Your Kafka Cluster with Minimal Downtime
Real-Time Data Transformation and Analytics with dbt Labs
What is the Future of Streaming Data?
What can Apache Kafka Developers learn from Online Gaming?
Apache Kafka 3.4 - New Features & Improvements
How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems
Git for Data: Managing Data like Code with lakeFS
Using Kafka-Leader-Election to Improve Scalability and Performance
Real-Time Machine Learning and Smarter AI with Data Streaming
The Present and Future of Stream Processing
Top 6 Worst Apache Kafka JIRA Bugs
Learn How Stream-Processing Works The Simplest Way Possible
Building and Designing Events and Event Streams with Apache Kafka
Rethinking Apache Kafka Security and Account Management
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