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Before building views for data analysis, the first question to answer is, “the reason, why you want a chart?” This section covers the different data visualizations we offer, and 17 chart types best suit your needs.

Comparison Charts

Comparison charts are most common and most easy-to-understand method for data analysis. These charts show a comparison between two or more data points and highlight their differences, trends, or patterns. For example, comparing previous year and current year’s annual revenues for your products and analyzing which products are performing well and which are failing. To create a comparison chart, you can create:

  • Bar Chart
  • Parallel Chart
  • Radar Chart
  • Gauge Chart
  • Table Chart

Composition Charts

Composition charts show how your data is composed, i.e., how individual parts make up the whole of something being analyzed. For example, analyzing countries based on ethnic and cultural diversity, sales division for a product in different regions. To create composition charts, you can use:

  • Pie Chart
  • TreeMap
  • Funnel Chart
  • Sankey Chart
  • Area Chart

Distribution Charts

Distribution charts show how data points are distributed or grouped over time and help you identify trends. For example, distribution of sex and age in a population, unemployment by sex and age groups, English speaking countries in the world, top wine producers in the world. To create distribution charts, you can use:

  • World Map
  • Heat Map
  • Shape Chart
  • Scatterplot
  • Boxplot

Trend Over Time Charts

Trend Over Time charts performs a comparative analysis to show how trends or patterns occur over time to determine future ones. For example, determining whether the stock market will continue to gain or lose. The users of these charts are mainly from the stock/forex/commodity markets, foreign exchange, investors, traders, financial institutions. To create trend over time charts, you can use:

  • Line Graph
  • Calendar
  • Candlesticks