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Advanced Excel Tricks every Data Analyst Should Know

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There are several types of data. It varies from scientific data to social statistical data. The choice of which tools to use depends on the field of study. Our concern is to evaluate briefly the data analysis using excel, its relevant field or associated field of use.

Data analytics tools and software are typically used to sort through academic, scientific and organizational statistical  data in order to identify patterns and establish relationships. These two things is what we refer to as Analysis.  Similar to “data mining,” data analysis techniques can help virtually any business gain greater insight into organizational, industry, and customer trends.

Analyzing data is an important tool to make decision in all sectors of life. An effective managerial, and governmental decisions are based on a well analyzed statistical data. So, the ability to analyze data is a powerful skill that helps you make better decisions. Data analysis using excel is one of the powerful tools to analyze data. It is not arguable to say that it is the most popular tools for data analysis with its built-in pivot tables. One other reason why it is popular is that you don’t any long period of training on Excel to deliver a simple excel data analysis. You are also permitted to use any supported version of Excel you have installed in your computer.

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There is no much use for a data that is collected at its raw form without any form of processing. It is almost useless at its raw form. This makes it highly important for many sectors and establishment that operates on mainly data mining Examples of this are the answers to examination questions that are collected from groups of students. There is simply no means by which you will know if the student fail or passed if no further analysis is done on the examination answers. It will even be difficult to know how the student performed with respect to the other. Data analysis using excel can perform a small programming that will grade their results.

It was discussed above that the data analysis using excel is not a very difficult thing to do. It is a very user-friendly software with a pleasant usability and user experience goals. It is possible to sort your data on one column or multiple columns. You can sort in ascending or descending order. Many other functionalities are found in the interactive platform that exists in an excel table. To get familiar with the interactive features of an excel is not a difficult task. Before anyone starts work on it, there is a need to study the important feature of an excel page. A little guide can be of help.  Below is a glance of a typical excel worksheet derived from Excel of version 2000.

excel worksheet

Figure 1: excel worksheet

Setting Up of an Excel

Before the analysis starts, after understanding the basic functionalities, there is a need to check that your data analysis tool pack has been loaded.  You can do this by selecting the Data tab; the Data Analysis command should appear in Analysis group on the right -hand side of the ribbon.  

Data Analysis tool pack

Figure 2: Data Analysis tool pack

Many advantages are being offered by excel analytical power.  For those new people in data analysis, there is a need to use some programming software to make analysis possible. Analysis that tackles the issue of the need to analyze based on the context of ” what -if” or what we can call “if – then”.  Don’t disturb yourself if it is a data-based analysis. Excel has removed the need to learn a software program as well as getting to grips with the analysis techniques. Excel also integrates easily into other Microsoft Office software products which can be helpful when preparing reports or presentations.

Many things can be done with an excel. To mention but few. As a  spreadsheet, Excel can be used for data entry, manipulation and presentation but it also offers a suite of statistical analysis functions and other tools that can be used to run descriptive statistics and to perform several different and useful inferential statistical tests that are widely used in business and management research. Typing of data and importation is allowed in the usage of an excel. 

Despite the wonderful functionality, there exist some limitations to excel data analysis: excel functionality does not cover many of the more advanced statistical techniques that are used in modern social and scientific research. More surprisingly, it lacks some common tools (such as boxplots) that are widely taught in basic statistics. There is also concern amongst some statisticians over the format of specific output in some functions. There are a lots of complaints due to the use of the extensive range of the template of graph that causes the improper color, 3-D display etc . Despite all these limitations. Excel remains a very valuable tool for quantitative data analysis as you will see. As oppose to these limitations, many basic analysis projects involving primarily data exploration, descriptive statistics and simple inferential statistics can be successfully completed using standard Excel. More advanced projects, especially those involving multivariate analysis are more challenging in 3 Excel and in such cases it is worth considering using specialist analysis software such as IBM SPSS.

Scientific Usage of Excel

With the above pros and cons, it is necessary ook to lat the impression of the scientists towards data analysis in excel. It has been noticed that many scientists gets delighted when in the disposal of an excel worksheet. Excel becomes a ubiquitous data tool that is being frequently accessed every day.  Many scientists use the functionality because of the data management functionality.

Database management systems are crucial to organizations and scientist. On a few data management, some of them prefer excel. Named ranges are a quick way to create a makeshift database in Excel. A named range is a table of data that has a label for easy reference. No need to get fancy: column headings across the top row and then rows of data below, following the typical structure of any data table. This gives the package a good potential.  There are several ways to assign your custom name to the table.  All you need do is to click in the top left corner and start typing. Put your primary key in the leftmost column and then use the VLOOKUP function anywhere in your workbook to find any value in your table.

Excel Ad-Ins for Scientific Use

The following are the ad ins that is suitable and available to be used by scientist should they decide to be using the tools:

Power Query:

Microsoft Power Query for Excel, is a new add-in that provides a seamless experience for data discovery, data transformation and enrichment for Information Workers, BI professionals and other Excel users.

Pivot Tables:

Pivot tables have been seen as one of Excel’s most powerful features. A pivot table allows you to extract the significance from a large, detailed data set. Despite the fact that excel is not as fully functional as a full-blown business intelligence tool, pivot tables in Excel is smart in quickly cross-tabulating data and calculating counts, sums, and other aggregate metrics.

Perhaps you might have been asking yourself about how fundamental it is while working with an excel, with your named range in place, click the pivot table button and then tell Excel where you want it to go. For small jobs, I’ll just put the pivot table next to the named range; for larger jobs, I’ll give the pivot table its own sheet. Just drag and drop columns, rows, and values to dynamically create your cross-tab analysis. It’s not Business Objects, but it’s not bad for a spreadsheet tool.

a pivot table

Figure 3: a pivot table

Solver Add-In:

This is very familiar to computer scientist. This tools use the power of the power of all the conditional statement used in all programming language. Solver is a what-if analysis tool for optimization. It is an add-in licensed from Frontline Systems that has shipped with Excel for many years.  Solver helps to find an optimal value in one cell, called the target cell, on your worksheet. It has three solving methods for solving spreadsheet optimization problems.

  • GRG Nonlinear: The GRG solver is used for solving smooth nonlinear problems. There is a new Multi-start search setting which when used in conjunction with the GRG solver results in better solutions, escaping locally optimal solutions in favor of globally optimal ones.
  • Simplex Method: The Simplex method can simply used for solving linear problems. The Simplex solving method has several performance enhancements in Excel 2010 resulting in greatly improved performance for some problem types.
  • Evolutionary Solver: The new Evolution solver accepts Solver models defined in exactly the same way as the Simplex and GRG Solvers, but uses genetic algorithms to find its solutions. A genetic algorithm is a problem-solving method of an artificial intelligence aspect of computer science. A major method in pattern recognition. While the Simplex and GRG solvers are used for linear and smooth nonlinear problems, the Evolutionary Solver can be used for any Excel formulas or functions, even when they are not linear or smooth nonlinear. Spreadsheet functions such as IF and VLOOKUP fall into this category.

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Analysis Toolpak

Social statistical data analysis uses this steps to some extent. It is a special microsoft excel plugins. If you need to develop complex statistical or engineering analyses, you can save steps and time by using the Analysis ToolPak. You provide the data and parameters for each analysis, and the tool uses the appropriate statistical or engineering macro functions to calculate and display the results in an output table. Some tools generate charts in addition to output tables.

The Analysis ToolPak includes the various tools some of them are described below.

  • Anova: This is an analysis of variance. The Anova analysis tools provide different types of variance analysis. The tool that you should use depends on the number of factors and the number of samples that you have from the populations that you want to test.
  • Descriptive Statistics: The Descriptive Statistics analysis tool generates a report of univariate statistics for data in the input range, providing information about the central tendency and variability of your data.
  • Fourier Analysis: An engineering mathematic analysis methods. It is interesting to see something like this being integrated as an ad-on for engineering data analysis in an excel. The Fourier Analysis tool solves problems in linear systems and analyzes periodic data by using the Fast Fourier Transform (FFT) method to transform data. This tool also supports inverse transformations, in which the inverse of transformed data returns the original data.

    Excel tools pack

    Figure 4. Excel tools pack

Excel Fuzzy Match:

The Fuzzy Lookup Add-In for Excel was developed by Microsoft Research and performs fuzzy matching of textual data in Microsoft Excel. In computer science, there is something called fuzzy logic. It is a scientific tools. It was partly incoporated as an ad-in to microsoft excel as well.  It can be used to identify fuzzy duplicate rows within a single table or to fuzzy join similar rows between two different tables. The matching is robust to a wide variety of errors including spelling mistakes, abbreviations, synonyms and added/missing data. For instance, it might detect that the rows “Mr. Andrew Hill”, “Hill, Andrew R.” and “Andy Hill” all refer to the same underlying entity, returning a similarity score along with each match. While the default configuration works well for a wide variety of textual data, such as product names or customer addresses, the matching may also be customized for specific domains or languages.

Summary 

Among many advantages offered  by the data analysis using excel, it is important to know that before you can use excel succesfully  and fastly, there might be a need for you to know some of the shortcut formulars and command,

Although the amont of time spent in loading the data into the field is much, which creates boredom, yet excel still offers a numbers of benefit to statistical researcher.

Excel has the ability to organize large amounts of data into orderly spreadsheets and charts quickly , It is  easy to enter and format the data , It has the ability to create the graphical or the visual representations of your data , And it is easy to integrate Excel with other business applications .

Excel can  be used for analysis and decision making ,  Excel allows the  professors to put the grades on a spreadsheet by numbers  which then allows the students to access the spreadsheet and view their grades on the exams and the quizzes. 

  • Data-Analytics


  • There are 6 comments


    • 7 months ago

      Disha   /   Reply

      Good information given about how one can analyse data analytics using excel and seek information about the work which is going on.Thanks for sharing the blog with us.

      • 6 months ago

        Sahil Arora   /   Reply

        Thanks Disha for sharing your experience.

    • 7 months ago

      Albert   /   Reply

      This is excellent information. It is amazing and wonderful to visit your site.thanks for sharing

      • 6 months ago

        Sahil Arora   /   Reply

        Thanks Albert for sharing your experience.

    • 7 months ago

      Sunil   /   Reply

      The information provided is good and hoping it will help in preparing the analytics report for websites.

      • 6 months ago

        Sahil Arora   /   Reply

        Off-Course Sunil it will help you to prepare your analytics report.

        All the best!!

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