Data Analysis Course for Business
- Identifying and understanding big data.
- Business Data analysis framework.
- Finding the probability of an event.
- Basic event relations and probability laws.
- Discrete and continuous variables.
- Probability distributions for discrete random variables.
- Probability distributions for continuous random variables.
- A continuous probability distribution: The normal distribution.
- Hypothesis testing for a single population.
- Producer's versus purchasing risk.
- Hypothesis tests when the variance is unknown.
- Hypothesis tests using proportions.
- Hypothesis tests for comparing two Populations.
- Single-Factor (One-Way) analysis of var: Independent Samples.
- Single-Factor analysis of Var: Randomized Blocks.
- Two-Factor (One-Way) analysis of Var: Independent Samples.
- Least squares method.
- Partitioning variability.
This session introduces two business analytical tools available in Microsoft® Excel® 2016: the Excel Data Model and Data Analysis Expressions (DAX).
The Excel Data Analytics Model enables audiences to include huge volumes of raw data from a range of sources into tables in your familiar Excel environment.
Audiences can create relationships between these tables and visualize raw data as business information. Data Analysis Expressions (DAX) provides a formula language, similar to the formula in Excel, though more powerful and streamlined in how it can manipulate data because it is designed especially for this analytical purpose.
In this Session audiences will learn how to import data in different formats into Microsoft® Excel®.
Audiences will see how to import CSV files, PDF files, in addition to importing multiple files from folders.
Audiences will also learn about creating queries using Query Editor in Excel 2016."
In this session, audiences will connect to a database and learn how to add data from other sources, such as text files.
Audiences will also complete the description of imported data by using relationships, hierarchies, and data tables.
In this session, audiences will see some more advanced features of Data Analysis Expressions (DAX) and use those features to create calculated columns and measures in Excel® Data Models.
Audiences will also see many of the most commonly used Data Analysis Expressions (DAX) functions and use them in formulas.
In this Session audiences will learn how to Create PivotCharts, Use cube functions, and construct graphs that can summarize the information retrieved by using cube functions.
After completing this session audiences will be able to describe Analytics, and Business Intelligence (BI), describes the process of big data analysis in Power Business Intelligence (BI), use the key visualizations in Power business Intelligence (BI) and describe the rationale for self-service Business Intelligence (BI).
After completing this session audiences will be able to describe the data model and know how to optimize your business analytical data within the model, connect to Excel files and import data.
Use on-premises and cloud Microsoft SQL server databases as data sources and take advantage of the Business Intelligence (BI) service by using Q&A to ask questions in a natural query language, and create content packs and groups.
This session introduces the analytical tools that are available for preparing your data and transforming it into a form ready for reporting.
This session enables business users to access corporate data, create and share reports and key performance indicators (KPIs) without dependency on a dedicated report developer.
Business users can use the Microsoft Power Business Intelligence (BI) suite of tools to connect to a wide variety of data sources.
These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake, and Azure Machine Learning—alongside Microsoft Excel® and other files, and software as a service (SaaS) providers such as Microsoft Bing®, Facebook, and MailChimp.
The combination of flexibility and the ability to create visually stunning, interactive data dashboards quickly makes Power Business Intelligence (BI) an obvious choice for any organization that needs to provide its users with a self-service BI solution."
During this session, audiences will use OLAP cubes database and models in reports and dashboards.
It doesn’t matter if audiences are using the Power BI service in the cloud, and an on-premises SQL Server Analysis Services implementation; the On premises data gateway enables live connections between the cloud and on-premises data servers.
After completing this program, audiences will be able to:
- Create and formatting measures and KPIs.
- Create PivotCharts, use cube functions, and construct graphs that can summarize the information retrieved by using cube functions.
- Build Excel Data Model, connect to databases, transform the data into a convenient form, and load the data into Excel tables or into the Data Model.
- Transform formatted Excel reports into usable data to perform further analysis.
- Describe the trends in BI, describe the process of data analysis in Power BI.
- Use the key visualizations in Power BI and describe the rationale for self-service BI.
- Use Q&A to ask questions in natural query language, and create content packs and groups.
- Use the Microsoft Power BI suite of tools to connect to a wide variety of data sources. These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake and Azure Machine Learning—alongside Microsoft Excel® and other files, and software as a service (SaaS) providers such as Microsoft Bing®, Facebook, and MailChimp.
- Goes behind the scenes of the visualizations, and explores the techniques and features on offer to shape and enhance your data, and create attractive reports, while helping to find hidden insights into data.
After completing this program, audiences will be able pass the following exams :
- Exam 70-779 : Analyzing and Visualizing Data with Microsoft Excel.
- Exam 70-778: Analyzing and Visualizing Data with Microsoft Power BI.
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