Heat Map as an Analysis Tool

1,746 views
1,617 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
1,746
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
16
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Heat Map as an Analysis Tool

  1. 1. Word from the Editor Dear GlobalMedNews reader, As part of our commitment to bring you up to date information about technological trends, this week’s feature article “Heat Map as an Analysis Tool”, describes a useful analysis tool which can be used in a variety of situations to visually analyze large amounts of data. Enjoy, Nitza Hauser Editor@GlobalMedNews.com Heat Map as an Analysis Tool Successful business is made by making the right decisions. Many of us are faced daily with either the need to make decisions or to support decisions made by management. Communicating the information needed to make the decision is usually more difficult than making the decision itself. Today’s article examines one of the growing numbers of visual techniques which helps in analyzing data and drawing conclusions. This technique can be used by analysts to better understand the data, by management to make decisions and as means of communications in support of decisions. Examples are varied, from the stock trader managing an investment portfolio through the researcher looking to map experiment results, to the hospital administrator analyzing billing data of “at risk” customers. Traditionally, the analyst made assumptions and then checked for statistical support of the assumption, but in this case the technique we chose to introduce to you today also allows for discovering new patterns and trends. Many software tools have been and are being developed to assist in data analysis tasks. Tools like spreadsheets and graphic presentation software help arrange the data in an easy to read format, enabling the user to view it in a form which will highlight the area of interest and importance. It is well known that it is easier for the human eye to work with graphs and pictures then with raw numbers. Therefore, the data analysis tools routinely utilize graphs and charts to present data. Recently, there has been a rise in interest in the use of heat map representations for analysis of large amounts of data. Heat maps are essentially a spreadsheet view of the data, where each cell has been colored according to a value scale. The unique feature of heat maps is, that they rely on the fact that our brains can distinguish shades of color many times faster than they can interpret and analyze numbers. The name ‘heat map’ is derived from the fact that the cell colors in the heat map table customarily range from red
  2. 2. (‘hot’) to blue (‘cold’), so that the more data is concentrated in a cell, the more red is the shade of that cell, making it ‘hotter’ and easier to identify. Heat map technology allows visualization of complex data relationships hidden in vast amounts of data. It is especially useful when comparing 2 large sets of data along a single comparison criterion and 2 attributes. For example, a portfolio manager wants to compare two sets of bonds (which may contain thousands of members each). He wants to arrange them by their industry sector and maturity, and then see how the two sets compare. Using a simple spreadsheet representation of the data, he might see something like Figure 1 below. Figure 1: Spreadsheet representation of data (courtesy eSpoc, Inc.) The X and Y axis of the table represent the attributes selected for comparison (Y-axis shows the industry sector, the X-axis shows maturity ranges). Each cell, or ‘bucket’, in the table then shows the difference in the comparison criteria (in this case number of members which fall in the cell) between the two bond sets. Obviously, it takes a while for the eye to locate the highest and lowest number points in such a table. Let us now compare the above table to the one shown in Figure 2 below. The most obvious difference is the added color gradient, which goes from red to blue, where deep red indicates the top member concentrations for one set of bonds, and deep blue indicates the cells where there is the highest member concentrations for the second set. Notice how easy it is to spot the areas of interest, which require action on the part of our hypothetical portfolio manager.
  3. 3. Figure 2: Heat map representation of data (courtesy eSpoc, Inc.) The investment industry is a good candidate for the use of heat maps due to the complexity involved. A heat map can:  Show the data by any chosen comparison criteria, (e.g., two portfolio returns, numbers of bonds in each portfolio) or risk parameters, such as durations or convexities.  Display any two arbitrarily selected comparison dimensions (e.g., maturity, industry sector, quality, or currency).  Aggregate portfolio members into sub-classes with similar characteristics for detailed comparison.  Show the specifics of each individual cell by clicking on it. Heat map is also a great tool for risk assessment, as explained by Dr. Lirov, CEO of eSpoc, Inc.: “The computational challenges of risk measurement and portfolio management rise exponentially with the size and the number of the investment portfolios and the diversity of asset classes in which they invest. One of the hardest problems for fixed income portfolio managers is the risk estimation of a portfolio and the return comparisons among several portfolios. Typically, fixed income portfolio risk managers estimate exposure of every security to a particular type of risk and then aggregate those risks across the portfolio holdings. Since the gap between assets and liabilities can be thought of as a portfolio consisting of a long position in assets and a short position in liabilities, the relative risk of a portfolio of assets vis-à-vis its benchmark is therefore computed as the risk of the gap portfolio.” Another use for this technology is in the area of error detection and quality checking for large amounts of data. Again, to borrow an example from the investment world, institutional investors money managers must obtain market data from an independent third party, raising the need for rigorous pricing quality checks. This is critical, since pricing errors have far reaching consequences which can distort valuation models, impair
  4. 4. relative value judgments, and lead to faulty risk measurements. Not surprisingly, with the growth of portfolio investment assets, pricing of individual securities becomes harder. Heat maps can provide for regular visual monitoring of price deviations. Specifically, for each security, the historical price change can be decomposed into components attributable to various risk factors (e.g., movements in the yield curve, risk-free returns, returns due to credit spreads). The heat map brings out the most substantial moves of the important components and enables quick fault indictment. In the biochemistry industry, for example, heat maps can be used by researchers analyzing experiment results. With hundreds of different conditions to test on hundreds or even thousands of genes, for example, the number of resulting data points can easily reach over one million. Using heat map analysis tools, a researcher can easily spot trends and even errors in the experiment. Data quality, is an area where heat map analysis can serve well, since it allows for the comparison of two large sets of data points. Another example is a heat map tool (called HEATMAP) developed by the Washington State Energy Office to perform a comprehensive simulation of existing and proposed district heating and cooling (DHC) systems. The model can map the entire DHC including the distribution system, customers load information, production plant information and may be used to study the economic feasibility of DHC and demonstrate the benefits in reduction of air emissions. As you can see, software tools utilizing heat map technology offer a strong analysis capabilities, and can serve in a variety of situations. eSpoc, Inc., for example, offers web based heat map tools as part of their overall suite of eSpoc Integration Services. By bundling data mining utilities with data analysis tools and tracking software, the users get a complete suite ideal for handling large amounts of data in a quick and efficient manner. Heat map analysis can also save a lot of time and effort, by allowing the user to easily make adjustments to the attributes and the comparison criteria for large volumes of data, and immediately view the results on the browser screen. Easily detecting trends and ‘hot’ spots requiring action allows managers to spend less time on their analysis and concentrate on the resulting action items. Question of the Week Have you ever used heat map analysis before?

×