According to research, a vast majority (94%) of large enterprises say data visualization and analytics are critical to their business growth and digital transformation. However, another study estimates business intelligence and analytics adoption hovers around 30% of all employees and given that staff are making decisions daily in response to customers’ needs, it is a missed opportunity not to involve them in the data journey.
Lack of data distribution throughout the enterprise produces reliance on business analysts and IT to inform strategic decisions. By raising awareness of data analytics and empowering all staff with training and technology, organizations can look forward to more intelligent decisions and greater overall business success.
In the world of big data, data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions.
There is no comprehensive history of data visualization, but we know it is not a modern development. The Lascaux Star map in France is believed to be 10,000 to 30,000 years old.
Data analytics is analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work on raw data for human consumption. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.
Universities are improving their data analytics programs using real-time dashboards. These gather and update student data profiles using multiple data points– from financial information to academic performance — to help advisers and faculty provide better support to students.
Some institutions are using predictive analytics – historical data collected over long periods of time that informs future choices. Universities can use predictive analytics models to help with several agendas: from improving recruitment and retention to meeting students’ needs. Though predictive analytics has been helpful for universities, the process requires a time commitment that does not always fit with educational institutions.
Data does not exist in a vacuum. In most organizations, countless hours are spent asking and answering “why” questions around key metrics. The information in any data source is only the first piece of the puzzle.
A controlled vocabulary is needed to ensure that the machine-assisted or fully automated indexing is comprehensive, regardless of what you are indexing. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies to make their information findable.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.