Data Visualization Analytics
Rich Graphical Representation of Complex Data Results.
Intuitive Presentation of Business Results and Trends.
Dynamic, Interactive Self-Service Information Generation and Manipulation.
- On-Premises, Remote, and Mobile Accessibility.
Data visualization refers to techniques used to communicate insights from data through visual representation. Its main goal is to distill large datasets into visual graphics to allow for easy understanding of complex relationships within the data. It translates sourced raw data into graphical such as tables, charts, graphs, and geospatial maps, presented upon data visualization dashboards. Converting complex data into intuitively comprehensible business intelligence.
Data visualization dashboards provide a single canvas upon which a mosaic of graphically rich, integrated information can be displayed. Allowing decision makers to interactively analyze and decipher patterns, trends and relationships within the data, as opposed to trying to figure out what is displayed and what it means.
Graphically rich self-serve data visualization dashboards are designed to engage the curiosity of decision makers into asking questions of the presented business intelligence. Promoting a fact based, measurable decision making environment, as opposed to one based upon subjectivity, opinions, and hunches. Providing a ‘one stop’, simplified means of telling intricate data stories, resulting in a ‘what-if’ driven decision making environment.
Data visualization technologies reduce the costs and delays in delivering decision support solutions. Speed is key, and data visualization aides in the understanding of vast quantities of data by applying visual representations to the data. They allow decision makers to source data from a vast range of on-premises and cloud hosted relational and non-relational data management technologies.
The visualization layer typically sits on top of a data warehouse or Data Lake, allowing users to discover and explore data in a self-service manner. Enabling them to self-sufficiently source and integrate disparate data types into graphical rich presentations.
Developing and publishing intuitive business intelligence data visualization dashboards involves minimal IT knowledge. Dashboard development generally follows a ‘drag and drop’ approach. Allowing consumers to rapidly become acquainted with the necessary techniques to mash raw data with graphical representations in meeting their informational requirements.
Backlogged IT departments are often unable to respond to time-sensitive requests within the available windows of opportunity. Companies who are able to gather and quickly act upon their data will be more competitive in the marketplace because they can make informed decisions sooner than the competition. Not only does this spur creativity, but it reduces the need for IT to allocate resources to continually build new models.
Data visualization technologies overcome IT resource related constraints by enabling decision makers to self-sufficiently access the right information at the right time. Creating a ‘win-win’ situation for both business and technology stakeholders. IT resources are allowed to focus upon high priority business initiatives requiring specialized technology skills. At the same time business decision makers are empowered with capabilities that allow them to promptly access the information they require to take address time-constrained business opportunities.
Enterprise data visualization solutions are implemented with technologies such as Microsoft Power BI and Tableau. The resulting dashboards can either be deployed within on-premises or cloud hosted environments, accessible via on-site or mobile devices. Allowing local and geographically dispersed decision makers to collaborate upon simultaneously delivered business intelligence.