Data Analysis

Using Data Analysis Expressions to solve common business problems in Power BI

Analyze business data, visualize insights, and share those insights across the enterprise

In this course, you will perform advanced data visualization and data blending with Tableau.

R is a functional programming environment for business analysts and data scientists. It's a language that many non-programmers can easily work with, naturally extending a skill set that is common to high-end Excel users. It's the perfect tool for when the analyst has a statistical, numerical, or probabilities-based problem based on real data and they've pushed Excel past its limits.

This course is designed for people who want to learn the Python programming language in preparation for using Python to develop software for a wide range of applications, such as data science, machine learning, artificial intelligence, and web development.

This course teaches concepts by deep-dive on-hand exercises. Throughout the course, you will learn data wrangling with hands-on exercises and activities. You’ll find checklists, best practices, and critical points mentioned throughout the lessons, making things more interesting.

In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service.

In this course, you will learn new concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS.

In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.

In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service.

In this course you will describe key database concepts in the context of SQL Server, characterize database languages used in SQL Server, describe data modeling techniques, discuss normalization and denormalization techniques, distinguish relationship types and effects in database design, describe the effects of database design on performance, and define commonly used database objects.

In this course, you will create single table SELECT queries, create multiple table SELECT queries, insert, update, and delete data, query data using built-in functions, create queries that aggregate data, create subqueries, create queries that use table expressions, use UNION, INTERSECT, and EXCEPT on multiple sets of data, implement window functions in queries, use PIVOT and GROUPING SETS in queries, use stored procedures in queries, add error handling to queries, and use transactions in queries.

In this course you will, create sophisticated SSIS packages for extracting, transforming, and loading data, use containers to efficiently control repetitive tasks and transactions, configure packages to dynamically adapt to environment changes, use Data Quality Services to cleanse data, successfully troubleshoot packages, create and manage the SSIS Catalog, deploy, configure, and schedule packages, secure the SSIS Catalog.

This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business.

In this course you will authenticate and authorize users, assign server and database roles, authorize users to access resources, use encryption and auditing features to protect data, describe recovery models and backup strategies, backup and restore SQL Server databases, automate database management, configure security for the SQL Server agent, manage alerts and notifications, managing SQL Server using PowerShell, trace access to SQL Server, monitor a SQL Server infrastructure, and import and export data.

In this course, you will learn how to leverage AWS data Services to store, process, analyze, stream, and query data to make decisions with speed and agility at scale, how to modernize data solutions end to end, and obtain skills to put your data to work to make better, more informed decisions, respond faster to the unexpected, and uncover new opportunities.

The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. Tableau® software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports.

This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases.

In this course, you will develop and deploy VBA modules to solve business problems.

If you are someone with existing SQL or SQL Server knowledge (or someone highly versed in different data repositories), this is the Power BI course for you. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI.