Democratizing the data lifecycle: Data visualization tools that drive impact

One of the most valuable assets an enterprise can tap into is its own data — sales transactions, web analytics, and input from third-party data sources. But the value this data holds will remain unrealized until it can be transformed into actionable insights. To unlock data-driven value, IT leaders must be able to quickly and easily explore data and share insights across teams at every stage of the data lifecycle.  

Data visualization is a critical first step for enterprise leaders to see and understand patterns, trends, and outliers in data, but it often encounters several roadblocks: data silos, integration complexities, and governance limitations. Without a unified view, data visualization can be incomplete or misleading, often resulting in ineffective decision-making.  

Impactful data visualization tools can help enterprises make the most of their data. By leveraging these tools and taking three simple steps, IT leaders can transform raw information into actionable insights. 

Enable self-service for full data lifecycle  

To get the full value from data, IT leaders need the full picture. Data engineers, business analysts, and data scientists must be able to collaborate across the data lifecycle, and access shouldn’t stop there. Organizations need to enable self-service analytics enterprise-wide. Data visualization tools should be designed to make data accessible to a broader range of users, not just analysts or data scientists.  

The most impactful data visualization tools give everyone across the data lifecycle the ability to present data analytics and machine learning models in meaningful ways. Organizations should focus on tools that are easy to use. For example, solutions like Cloudera Data Visualization offer intuitive drag-and-drop capabilities, infused AI, and custom application creation.  

Perhaps most importantly, tools should offer integrated security and governance, so users can leverage enterprise data without moving, copying, or creating security gaps. That way, with secure collaboration and transparency across teams, more users are empowered to make data actionable, while ensuring they are viewing data that they should have access to. 

Ensure secure, seamless integration 

Today, most enterprises have shifted to a hybrid cloud environment in some form. With a hybrid approach, organizations are faced with the challenge of managing data across a growing number of environments, and as data and analytics move between infrastructures, the tools that effectively manage it in one environment may not translate to another. When it comes to data visualization tools, data needs to be integrated seamlessly across hybrid and multi-cloud environments. For enterprise leaders, that means leveraging tools that are built to work across diverse data environments, including on-premises systems, private clouds, and public cloud services. 

The focus should also be on tools that work out-of-the-box without requiring extra integration, moving data, or compromising security. This way, users can be more agile and reduce barriers to deliver insights to their peers and broader business teams. Additionally, native integration offers particular benefits for managing user access and governance. Users can log into the data visualization tool and start analyzing the data they have access to, removing the need to replicate policies across multiple tools. Keeping data in one central place, such as a consolidated Open Data Lakehouse, helps prevent data leaks and strengthens enterprises’ security and governance throughout. 

Deliver real-time insights 

Part of what makes a data visualization solution, like Cloudera’s, so impactful is the ability to deliver raw information to users’ fingertips instantly. Advanced capabilities might include real-time streaming visualizations, embedded machine learning, and natural language querying. Gone are the days when writers built reports using back-end SQL for their end users. Today’s business users can talk directly to their data in natural language and gain the insights they need immediately. Automated reporting is also especially helpful, enabling users to automate analytics dashboards for updates and consumption.  

Data visualization should be designed to bring together and drive augmented analytics by surfacing visual analytics across all these sources of data. In a single dashboard or application, users can bring in a pie chart from a data warehouse, a table showing results of a faceted search, or prediction results from a deployed ML model. 

Bring data visualization and true hybrid together 

Embracing data visualization is about more than just maximizing the value of data. It’s also a powerful means to create trust and confidence in analytical outputs and machine learning models, helping to operationalize those insights across the business. As enterprises adapt their data management and infrastructure, embracing a true hybrid approach, they must leverage tools that are scalable and secure.  

Learn more about how Cloudera’s data visualization capabilities are fueling better decision-making and collaboration.