
Nearly every organisation bases its key decisions on sound data. This data may have been generated from the past reports or may comprise future projections. The data initially collected is just a bunch of numbers and statistics. It bears no meaning to managers until it is converted into suitable information. Data visualization allows the conversion of this information into a pictorial representation which is much easier to understand and read. These visual representations might be in the form of graphs, charts, maps, videos, dashboards, or any type of visual format. This enables rapid identifying of trends and patterns present in the data that would otherwise have been difficult to recognize and understand.
Why is data visualization important?
The human brain can comprehend a visual data set much easier than rows and rows on a spreadsheet. Since data has become such an integral part of strategic decision-making for any organisation, data visualization has spiraled to every sphere where data is utilized.
How can Data Visualization be made good? How to position the data, use the color scheme and other techniques to enhance the readability of the data? How to achieve data cleansing for data better visualization ? What are different tools available for data visualization ? Which tool will be suitable for which data set? Data visualization is not merely the plotting of charts and tables but requires acute preparation beforehand in the form of these questions. Data visualization is a subtle science and art. It requires comprehension of raw data and apt application of visual tools meticulously enough to draw valuable insights from the dataset.
Training has brought a sought-after Data Visualization course that elaborates both the science and art part of data visualization . Numerous available tools have been discussed in detail along with their application, pros, and cons. Professionals from all fields experience the vital need of presenting their data in a convenient form to prolifically state their points and derive enhanced understanding from it. This course is mindful of this requirement and therefore discusses important features, techniques, and concepts related to data visualization in the most beneficial manner.
Module 1: Why data visualization ?
Module 2: Data Visualization Process
Module 3: Use of Mapping
Module 4: Use of Bar Graphs
Module 5: Use of Pie Charts
Module 6: Use of Histograms
Module 7: Use of Line Graphs
Module 8: Use of Scatter Plots
Module 9: Challenges in Data Visualization
Module 10: Current Trends
Module 11: Excel Activity
Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).
At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.