What is a “bad chart”? Based on this collection of curated "bad charts", it is not easy to nail down “bad-ness”. We can all give in to the fact that Microsoft’s Excel has made our lives easy with its charting options.
Salesforce paid $15 Billion for Tableau and Google $2.5 Billion for Looker. Did they sense the need for a good visualization tool? Unequivocally we can all give in to the fact that Microsoft’s Excel has made our lives easy with its charting options. Select the data, choose the graph of your choice and there you have it, a graph to appeal. So why did the two technology giants spend billions for a charting tool? This will be our quest in this write-up.
With the amount of data being injected every day, the need for great visualization tools completely justifies the prodigious amount the companies are willing to pay. Analysing data, looking for patterns, and visualizing it has become the modus operandi to win in any market. But if pouring in billion dollars would have created the impact, Google or Salesforce would have their charts all over the world but many from the visualization community would agree that publications such as The Economist, Financial Times, HBR are second to none.
‘What is a Good Graph?’. It is an important question and should be answered using both a ‘Bad’ Chart and a ‘Good’ Chart. What better than to visualize it, the table below has the data about the banking index for few banks along with ‘Our’ bank — Financial Services.
Visual Analytics and Advanced Data Visualization - How CanvasJS help enterprises in creating custom Interactive and Analytical Dashboards for advanced visual analytics for data visualization
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
How to use graphs effectively while working on Analytical problems. Data visualization is the process of creating interactive visuals to understand trends, variations, and derive meaningful insights from the data. Data visualization is used mainly for data checking and cleaning, exploration and discovery, and communicating results to business stakeholders.
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A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.