#Data analysis excel 2018 how to#
#Data analysis excel 2018 professional#
#Data analysis excel 2018 free#

Thank you for reading my blog, if you have any questions please mention in the comments and hit the like button if you like my write up.Using Excel for Business and Financial Modelling by Danielle Stein Fairhurst A hands-on guide to using Excel in the business context First published in 2012, Using Excel for Business and Financial Modelling contains step-by-step instructions of how to solve common business problems using financial models, including downloadable Excel templates, a list of shortcuts and tons of practical tips and techniques you can apply straight away. Let us see some more techniques of data modeling and data transformation in my next blog. We have seen few techniques of data modeling in Power BI using Power BI desktop in this blog. Once you practice, more features can be explored. This way you would be able to achieve relationships in tables, tables can be from different data sources. You can edit existing relationships or create new ones based the data and type as many to one, one to one etc if you click on the Manage relationships or click on the icon on side bar, you can see the relationships as shown in below snippetīy default, Power BI identifies below relations in the tables, based on our requirement and understanding, we can create more relations as we are used to create in SQL server management studio Power BI desktop automatically identifies the relationship in the tables based on the identical columns. We have different tables and would need to some connect between the tables for better visualizations. Similarly we can use other location fields and change their category to use those in geographical visuals. Once City is selected, you would see one icon near column and this column can be used to show the geographical visuals. You can see there are various standard options to categorize your data columns for ease of reporting such as Address, City, Continent, Region, Longitude and Latitude etc It is showing uncategorized, however we want Power BI to identify this as a location i.e. Select the CityName column and look at the data category. Kindly refer the below screenshot for next step. To achieve this, you can click on either Modeling menu or click on data icon on the left side bar as shown in above screenshot. Such information is available in Match table, however we have do to few changes in the data category so that it is identified as geographic locations. Let us say we want to show the number of matches played per location. Referring to below screenshot, let us click on the Modeling. Once we get data from these excels in tables, we can start with data modeling. As mentioned in earlier posts, we will upload these five excels in Power BI desktop and start developing the report. We will create the reports as shown in below snippets.

The names are really intuitive to understand the content of the data. Here I got five CSV files consisting of various information of the IPL matches. Hence this data consists of ball by ball details of the matches played until last year along with details about the teams, players etc.

#Data analysis excel 2018 professional#

Those who do not know what is IPL, it is a professional Twenty20 cricket league in India contested during April and May of every year by teams representing Indian cities and some states. Let us start how we can develop efficient and beautiful reports in Power BI with IPL Data.

I am using the data source for IPL from 2008 to 2017 which is freely downloadable from the internet.

#Data analysis excel 2018 free#

You can get free data sources for analysis, POC purposes on internet as mentioned below. Thanks to Ashish for this creative work and inspiring me to write this post. I was looking for good example to explain Power BI capabilities and recently saw one excellent Power BI case study on IPL which is Indian Premier League analytics by ashishrj which can be referred below: Now let us go ahead, do some data modeling and data transformation for this data before we start developing reports. In my previous blog we have seen how to connect to excel files to get the data.