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What does it take to be a great data scientist?  Some of these you undoubtedly know without looking, but others may surprise you. These six hard and soft skills are not just things to look for in a data science hire, but are also things to cultivate in yourself to prepare for a successful and fulfilling career in data science. 1. Statistical thinking Data scientists are professionals who turn data into information, so statistical know-how is at the forefront of our toolkit. Knowing your algorithms and how and when to apply them is arguably the central task to a data scientist's work. However, to do this well can be an art and a science. A good data scientist can model any data he is given and implement a toolbox full of algorithms to make statistically-informed predictions and recommendations. A great data scientist can smell something 'fishy' in the results she gets, senses that he needs to ask the client or stakeholder a few more questions before retreati

Learning Advanced Excel - Needed to Explore Data, understand patterns & themes on the data... Below will help you become a good Data Analyst on Excel What is Latest Excel Version  Maximum Rows & Columns Calculated Columns Casting / Conversion of Data Types Especially working Text to Numbers, Extracting Year, Month, Date from a single datetime or date column Converting / changing / bringing a single time zone for multiple timezone data String operations - Extracting only a portion of your value Statistical Functions in Excel Banding a value available in a single column Pivot Tables - SO IMPORTANT and need to go deep into various features available on a Pivot Table Pivot Charts Using Slicers with Pivot Tables Using Filters with Pivot Tables Using Sorting inside Pivot Tables Moving around Rows & Columns and understanding themes in your data VLookup HLookup When to use Lookups Bringing values / columns from multiple excel sheets into a single sheet W

 1) Keywords - you should know what each of these mean, when you learn PBI. Power BI Licensing: Free, Pro, Premium Power BI Cloud and Power BI On-Premise (Power BI Report Server) Power BI Desktop and how to use it Ways to bring in data - Import Data, Direct Query and Live What is SSAS Tabular and why PBI with SSAS Tabular model is great combination Size limitations when you do Import Data # of times you can refresh data in a day  - when you do Import Data Building Blocks of PBI - DataSets, Dashboards, Reports, Tiles, Visualizations Slicers Filters and difference with Slicers What is DAX and DAX Expressions  Custom Columns Custom Measures and difference with Custom Columns Data Modeling within PBI Desktop Certain basic business expectations - how do you do it in PBI - Bringing in YTD, MTD, Doing Trends, Comparing YoY, MoM Using Maps Using InfoGraphics Custom Visuals and how to use them SQL Server latest version SQL Server various Editions Writing basic