A dashboard for data analytics is a tool used to multi-task, organize, visualize, analyze, and track data. The overall purpose of a data analytics dashboard is to make it easier for data analysts, decision makers, and average users to understand their data, gain deeper insights, and make better data-driven decisions.
Data dashboards are designed to connect and help extract important information from a wide variety of different data sources, services, and APIs. This information is displayed in a single, unified view via visuals such as charts, figures, graphs, and tables. An organization can have a different customizable dashboard for each department and even a dashboard for each individual project, which helps provide granular monitoring of very specific KPIs.
“Smart” data analytics dashboard software uses AI and Machine Learning to save time and automate processes like data collection, discovery, preparation, replication, and reporting, which is crucial for big data sets where manual processing is impractical. Advanced interactive dashboards will provide compelling storytelling through attractive designs and real-time, interactive dynamic data visualizations that empower team members to quickly and easily reveal hidden insights and draw valuable conclusions that can help answer business questions and informa business decisions.
There are three types of data analytics dashboards: operational, strategic, and analytical.
There are many different benefits to be gained from the many different kinds of data analytics dashboards. Some of the most common benefits include: data visibility and accessibility, measuring performance, business forecasting abilities, and agile responses:
Big data analytics is leveraged in nearly every modern industry. Some big data analytics examples include retail, manufacturing, oil and gas, government, healthy industries, education, sports, sciences, airlines, banking, business analytics dashboards, and marketing analytics dashboards. All of these industries can benefit enormously from data analytics dashboards tailored to their specific needs. Read on to see some data analytics dashboard examples and data analytics demos.
Companies throughout the oil and gas industry can derive enormous value from big data analytics dashboards. Industry professionals can interact with spatiotemporal data analytics in energy to determine things like productivity drivers, assess suitable land, and understand benchmark performance.
Oil industry professionals can visually analyze data and conclude why wells are over or underperforming, forecast their estimated potential, compare daily drill and well performance, manage fleets, and identify production trends across basins. Dashboards for data analytics can help renewable energy industry professionals visualize and interact with massive multi-sourced datasets to determine where their customers should make wind, solar, biomass, hydroelectric, or geothermal energy investments.
In this oil and gas demo, visualizations for 250 million well production records across the entire United States are available for analysis. Research scenarios and quickly analyze production decline performance, correlations, and rate of change with a few clicks.
Covid-19 data maps updated with real-time information were crucial for tracking the spread of the pandemic, recovery rates, and monitoring the effectiveness of quarantine orders and mask mandates. Covid-19 data analytics dashboards provided a simple, unified view of cases around the world filtered across location and time, informing decisions made by hospital administrators and lawmakers, such as office, school and business closure orders; mask mandated spaces; travel bans; PPE inventory forecasts; and more.
Government data analytics dashboards compile data from a wide variety of sources, like hospitals, government agencies, the CDC, World Health Organization, and make it easier for users to quickly identify patterns and draw conclusions.
In this Covid-19 demo, visualize the spread of the virus using maps and charts, compare the growth of cases across various countries and US states, and analyze the recovery rate in various regions of the world.
Census data helps inform a wide variety of critical decisions, like where to build schools and hospitals, how to distribute funds and assistance throughout the states, highway planning and construction, electoral redistricting, apportionment of representatives, and much more. The sheer volume of individuals and their corresponding information would be daunting in a spreadsheet - even when trying to understand census undercount. Factors like population growth, sex, age, marital status, education, race, occupation, income, rent and utilities, language, citizenship status, military status and more are recorded for hundred of millions of people over the course of several years.
These massive datasets are only as valuable as our ability to comprehend them. Data analytics dashboards make census data digestible and valuable with easy-to-read, interactive data visualizations like dot density maps. The average user should be able to easily identify and understand changes in their community and around the country.
In this demo, uncover insights about the American people and workforce on 38M+ rows of 2000-2015 US Census Bureau American Community Survey (ACS) Public Use Microdata Sample data and US Census ACS Data with 400+ columns.
The quality, variety, and volume of data analytics dashboard tools has increased in recent years. The best option for your organization depends on a number of factors, such as budget, deployment, client, and the specific goals and objectives of the project at hand. There are three main types of dashboard software: operational, strategic, tactical, and analytical. Analytical dashboard software functionality is prevalent in many business intelligence tools as they provide the greatest value to data analysts and data scientists. Learn how to make the most out of your business intelligence dashboard here.
The best data analytics dashboard tools will offer: the ability to connect your data from multiple sources, embedding capabilities, self-service reporting, automated real-time updates, streaming and predictive analytics driven by AI, filtering across time and location, interactive visual analytics, full customization, and at-a-click exploration. Some examples of popular enterprise analytics dashboard software include: HEAVY’s visual analytics platform, Izenda, Periscope Data, Dundas BI analytics dashboard, Microsoft Power BI, IBM Cognos, TIBCO Spotfire, Looker, and Sisense.
Every data analytics dashboard will look different depending on each different project’s goals and objectives. The best option will be one that empowers you to be at one with your data and to interact with it instantly and effortlessly. See the key capabilities that OmniSci’s converged analytics platform provides to help users achieve insights from your largest datasets at the speed of curiosity.