Best Data Warehouse Courses

Find the best online Data Warehouse Courses for you. The courses are sorted based on popularity and user ratings. We do not allow paid placements in any of our rankings. We also have a separate page listing only the Free Data Warehouse Courses.

Master Data Management

Learn about the basics of Master Data Management within organizations

Created by Adastra Academy - Emerging Data Management and Analytics Technology Educators

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Students: 31878, Price: Free

Students: 31878, Price:  Free

This introductory level course provides students with a high level understanding of Master Data Management. Master Data refers to having a single copy of a data record for an organization to ensure that the proper data quality measures are in place. Master data also ensures consistency of reporting across all multiple lines of business within an organization.

This course highlights key Master Data Management concepts, methodologies, and processes including definitions, examples, common master data challenges, architecture considerations, types of master data projects, the data mastering process, and matching and merging techniques. The course also touches on best practices of master data storage within a repository structure.

The main items explained in this course include:

  • What are the main concepts of Master Data
  • What are the main concepts of Master Data Management
  • What are the Master Data Management challenges within organizations
  • What are the main Master Data Management architectures

Essentials of Data Science

Discover what Data Science is all about

Created by Maximilian Schallwig - Data Scientist

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Students: 25288, Price: Free

Students: 25288, Price:  Free

Data Science is growing ever faster as Big Data become an increasingly important part of our lives.
Because data is universal, the applications of Data Science are pretty much endless, all you need is access to the data of the system that you want to study.

Since it's such a new field, there are a lot of questions about what is Data Science, what do Data Scientists do, and what do you need to succeed as a Data Scientist? 

This course is designed to give you an overview of the three essential areas of Data Science, the areas that every good data scientist should know, and being proficient in these areas can be the key to your success. After this course you will have a clear understanding of what Data Science is all about, and can make a clear decision of if it's the right field for you. You will also know what areas are important in Data Science, and hence can make informed decisions on what areas to focus on learning.

When you really get into Data Science there are other areas that start coming in too, but all of these can be traced back to one, or multiple, of these three basic foundations.

Snowflake Datawarehouse & Cloud Analytics – Introduction

Build a turbo-powered Cloud Data Warehouse using Snowflake

Created by Nav p - Cloud Data Engineer

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Students: 23544, Price: Free

Students: 23544, Price:  Free

Cloud Data Warehouse is the next big thing. Learn What is Snowflake Cloud Data Warehouse and its architecture.  Build highly scalable, high performance next-gen modern data warehouse for you company.  The course is designed in beginner friendly, helping you to understand the basics of cloud, SAAS and it all works together in the background.

Requirements:

  • Good to have prior data warehouse experience, but not mandatory

  • Nice to have SQL Background, but not mandatory

Data Warehouse Fundamentals for Beginners

Best Practices and Concepts for Architecture and Dimensional Design

Created by Alan Simon - Thought leader in business intelligence and enterprise data

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Students: 21995, Price: $44.99

Students: 21995, Price:  Paid

If you are a current or aspiring IT professional in search of sound, practical techniques to plan, design, and build a data warehouse or data mart, this is the course for you.

During the course, you’ll put what you learn to work and define sample data warehousing architectures and dimensional data structures to help emphasize the best practices and techniques covered in this course. Each section has either scenario based quiz questions or hands on assignments that emphasizes key learning objectives for that section’s material. This way, you can be confident as you move through the course that you’re picking up the key points about data warehousing.

To build this course, I drew from more than 30 years of my own data warehousing work on more than 40 client projects and engagements. I’ve been a thought leader in the discipline of data warehousing since the early 1990s when modern data warehousing came onto the scene. I’ve literally seen it all...and written about the discipline of data warehousing in books such as the original Data Warehousing For Dummies ® , along with articles, white papers, and as a monthly data warehousing columnist. I’ve led global consulting practices delivering data warehousing (and its related discipline, business intelligence) to some of the most recognizable brand name customers, along with smaller-sized organizations and governmental agencies. My own consulting firm, Thinking Helmet, Inc., specializes in data warehousing, business intelligence, and related disciplines. I’ve rolled up my sleeves and personally tackled every aspect of what you’ll learn in this course. I’ve even learned a few painful lessons, and have built a healthy share of “lessons learned” into the course material.

In this course, I take you from the fundamentals and concepts of data warehousing all the way through best practices for the architecture, dimensional design, and data interchange that you’ll need to implement data warehousing in your organization. You’ll find many examples that clearly demonstrate the key concepts and techniques covered throughout the course. By the end of the course, you’ll be all set to not only put these principles to work, but also to make the key architecture and design decisions required by the “art” of data warehousing that transcend the nuts-and-bolts techniques and design patterns.

Specifically, this course will cover:

  • Foundational data warehousing concepts and fundamentals

  • The symbiotic relationship between data warehousing and business intelligence

  • How data warehousing co-exists with data lakes and data virtualization

  • Your many architectural alternatives, from highly centralized approaches to numerous multi-component alternatives

  • The fundamentals of dimensional analysis and modeling

  • The key relational database capabilities that you will put to work to build your dimensional data models

  • Different alternatives for handling changing data history within your environment, and how to decide which approaches to apply in various situations

  • How to organize and design your Extraction, Transformation, and Loading (ETL) capabilities to keep your data warehouse up to date

Data warehousing is both an art and a science. While we have developed a large body of best practices over the years, we still have to make this-or-that types of decisions from the earliest stages of a data warehousing project all the way through architecture, design, and implementation. That’s what I’ve instilled into this course: the fusion of data warehousing art and science that you can bring to your organization and your own work. So come join me on this journey through the world of data warehousing!

What is Data Science ?

Fundamental Concepts for Beginners

Created by Gopinath Ramakrishnan - Data Science & Machine Learning Enthusiast, Agile Coach

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Students: 19599, Price: Free

Students: 19599, Price:  Free

If you have absolutely no idea what Data Science is and are looking for a very quick non-technical introduction to Data Science , this course will help you get started on fundamental concepts underlying Data Science.

If you are an experienced Data Science professional, attending this course will give you some idea of how to explain your profession to an absolute lay person.

There are lots of very good  technical and programming focused courses available on Data  Science in Udemy and elsewhere.

This short  course will lay a firm foundation for better understanding and appreciation of what is being taught in advanced Data Science courses. 

Data Warehouse Developer-SQL Server/ETL/SSIS/SSAS/SSRS/T-SQL

Develop and Implement a Data Warehouse Solution Step by step

Created by Bluelime Learning Solutions - Learning made simple

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Students: 17582, Price: $39.99

Students: 17582, Price:  Paid

This course describes how to  design and implement a data warehouse solution.
students will learn how to create a data warehouse with Microsoft SQL Server implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

The Primary responsibilities of a data warehouse developer include:
Implementing a data warehouse.
Developing SSIS packages for data extraction, transformation, and loading.
Enforcing data integrity by using Master Data Services.
Cleansing data by using Data Quality Services.

Prerequisites :

Experience of working with relational databases, including:
Designing a normalized database.
Creating tables and relationships.
Querying with Transact-SQL.
Some exposure to basic programming constructs (such as looping and branching).
An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.

Students will learn how to :

••Deploy and Configure SSIS packages.
••Download and installing SQL Server
••Download and attaching AdventureworksDW database
••Download and installing SSDT
••Download and installing Visual studio
••Describe data warehouse concepts and architecture considerations.
••Select an appropriate hardware platform for a data warehouse.
••Design and implement a data warehouse.
••Implement Data Flow in an SSIS Package.
••Implement Control Flow in an SSIS Package.
••Debug and Troubleshoot SSIS packages.
••Implement an ETL solution that supports incremental data extraction.
••Implement an ETL solution that supports incremental data loading.
••Implement data cleansing by using Microsoft Data Quality Services.
••Implement Master Data Services to enforce data integrity.
••Extend SSIS with custom scripts and components.
••Databases vs. Data warehouses
••Choose between star and snowflake design schemas
••Explore source data
••Implement data flow
••Debug an SSIS package
••Extract and load modified data
••Enforce data quality
••Consume data in a data warehouse

The volume of data available is huge and increasing daily. Structured Query Language -SQL (pronounced as sequel) is the standard language used to communicate and interact with data stored in relational management database systems like Microsoft  SQL Server Oracle, PostgreSQL,MySQL etc.

Different database management systems have their own proprietary  version of the SQL language  but they all conform to using some commands in SQL the same way.   Microsoft SQL Server's version of SQL is known as Transact-SQL  (T-SQL).

You will learn the basics of the SQL language and Transact-SQL since  both use certain commands in the same way.

What You will learn includes:

  • Installing SQL Server

  • Install SSMS

  • Basic Database  Concepts

  • Creating Database

  • Creating Table

  • Creating Views

  • Creating stored procedures

  • Reading data from a database

  • Updating database records

  • Backing up database

  • Deleting Records

  • Truncating Table

  • Dropping Table

  • Dropping Database

  • Restore Database

Data Warehouse Concepts: Basic to Advanced concepts

Data Warehouse Concepts: Learn the in BI/Data Warehouse/BIG DATA Concepts from scratch and become an expert.

Created by Sid Inf - Data/ETL Architect

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Students: 11324, Price: $119.99

Students: 11324, Price:  Paid

In this course, you will learn all the concepts and terminologies related to the Data Warehouse , such as the OLTP, OLAP, Dimensions, Facts and much more, along with other concepts related to it such as what is meant by Start Schema, Snow flake Schema, other options available and their differences. It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse. Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically. You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL. Upon completion of this course, you would have a clear idea about, all the concepts related to the Data Warehouse, that should be sufficient to help you start off with the next step of becoming an ETL developer or Administering the Data warehouse environment with the help of various tools. All the Best and Happy Learning !

Data Warehouse Development Process

Specific aspects of Data Warehouse Development Process

Created by Sid Inf - Data/ETL Architect

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Students: 11106, Price: $49.99

Students: 11106, Price:  Paid

Data is the new asset for the enterprises. And, Data Warehouse store the data for better insights and knowledge using Business Intelligence. Development of an Enterprise Data Warehouse has more challenges compared to any other software projects because of the 

  • Challenges with data structures
  • The way data is evaluated for it's quality
  • Complex business rules/validations
  • Different development methods (various SDLC models like Water Fall model, V model, Agile Model, Incremental model, Iterative model)
  • Regulatory requirements for various domains like finance, telecom, insurance, Retail and IME
  • Compliance from third party governing bodies
  • Extracting data for various visualization purposes

In this course, we talk about the specific aspects of the Data Warehouse Development process taking real time practical situations and how to handle them better using best practices for sustainable, scalable and robust implementations.

Data Warehouse basics for absolute beginners in 30 mins

Data Warehouse basic concepts like architecture, dimensional modeling, fact vs dimension table, star vs snowflake schema

Created by Eshant Garg | LearnCloud.Info | 80,000+ Enrollments - Instructor | LearnCloud.Info | AWS | Azure

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Students: 9678, Price: Free

Students: 9678, Price:  Free

Important Note:

Please note that this is NOT a full course but a single module of the full-length course, and intended to cover very basic fundamental concepts for absolute beginners so that they can speed up with Azure Synapse SQL Data Warehouse course.

This module is NOT GOOD for you if:

  • You are already experienced in this technology

  • You are looking for an intermediate or advance concepts

  • You are looking for practical examples or demo

This module is GOOD for you if:

  • You want to understand the basic fundamental concepts of this technology.

This is a free module to help others. If you are not in the intended audience, I request you to please feel free to unenroll.

Where I can find a full-length course?

Please look at the bonus lecture in the end.

What will students learn in this course?

  • Microsoft SQL Data Warehouse (Crash course to speed up with Cloud warehousing)

Level

  • Beginners

Intended Audience

  • Anyone who wants to start learning Data warehousing

Language

  • English

  • If you are not comfortable in English, please do not take the course, captions are not good enough to understand the course.

Target Students

  • Database and BI developers

  • Database Administrators

  • Data Analyst or similar profiles

Prerequisites

  • Basic T-SQL and Database concepts

Course In Detail

Data Warehouse Crash Course

  • In this module, you will learn, what is Data Warehouse, Why we need it and how it is different from the traditional transactional database.

  • We will learn the concept of dimensional modeling which is a database design method optimized for data warehouse solutions.

  • Then I will explain what we mean when we say facts and their corresponding fact tables. What are the dimensions and their corresponding dimension tables?

  • how are these special kinds of tables joined together to form a star schema or snowflake schema?

  • This section will establish the foundation before you start my course on Azure Synapse Analytics or formally known as Azure SQL Data Warehouse.

[Tags]

Microsoft SQL Server, Azure SQL Server, Azure SQL Data Warehouse, Data Factory, Data Lake, Azure Storage, Azure Synapse Analytics Service, PolyBase, Azure monitoring, Azure Security, Data Warehouse, SSIS

Implementing a Data Warehouse with SQL Server 2012

Implementing a Data Warehouse with SQL Server 2012 (Exam 70-463)

Created by Compaq learning - One stop to learn and succeed

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Students: 6601, Price: $84.99

Students: 6601, Price:  Paid

Adding to its data management system Microsoft has come up with a new Server, Microsoft SQL Server 2012 which familiarizes us with the construction and usage of databases in SQL Server platform. This course is the successor of Microsoft SQL Server 2012, a step higher into the administration of the data sytem. It is an excellent platform for students to build and implement a data warehouse. The course intends to target all data professionals including data analysts and other aspiring professionals who wants to get ready for exam 70-463, also known as Implementing a Data Warehouse with SQL Server 2012.

Towards the end of this course our participants will have a thorough knowledge on data warehouses and the uses of dimensions. Apart from that our learner will also understand the importance of Fact Table along with the various concepts that are involved in the implementation of Data Warehouse with SQL Server 2012. This course also looks into the different elements of Control Flow and allows the learner to comprehend how to work with variables. In this course you will learn about the different types of Transforms available in SSIS, apart from how to deploy and manage packages. Finally you will understand how to debug and secure packages.

This course is that is the basis for all other SQL Server-related disciplines—Database Development, Database Administration, and Business Intelligence. The main idea of this course is to make our students cognize SQL Server 2012 databases administration. You will be comprehending a lot about the various issues and other decisions that are part of SQL Server installation and configuration. SQL Server 2012 is a prevailing platform that is widely used in the enterprise and cloud. There are many critical systems based on it. This Exam 70-463 is also a part of the series of certifications to master this platform.

Apart from this as a student you will keen to look into the various operations involved including building and managing data warehouse and architecturing and implementing dimensions.

You will also find it both challenging and interesting to work with various variables. There will also be a discussion on some of the important topics namely, instance, database and object security strategies. You will be also interested in implementing and automating ETL Solution. Some of the high availability technologies will also be discussed as part of the training by looking into deploying and managing packages along with debugging and securing them

Our training is broken down to 90 lecture sessions that will cover all objectives. As add ons, we are also providing demos on other major concepts so that participants understand how the steps learned are implemented in real time.

Azure SQL Data Warehouse Synapse Analytics Service

Cloud Data Warehouse in Azure Synapse Analytics Service (formerly Azure SQL Data Warehouse). [Covered: DP-200, DP-201]

Created by Eshant Garg | LearnCloud.Info | 80,000+ Enrollments - Udemy Instructor | LearnCloud.Info | AWS | Azure

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Students: 5188, Price: $24.99

Students: 5188, Price:  Paid

Why Azure Synapse Analytics Service  (formerly Azure SQL Data Warehouse)

  • Azure Synapse Analytics truly is a game-changer in Data processing and Analytics.

  • In the most recent study conducted by GigaOm in January 2019 for the TPC-H benchmark report shows that Synapse Analytics is 14 times fast and still 94% cheaper than any other leading service in the market.

  • And that's why clients are shifting to Azure and Azure is growing at nearly twice the rate of Amazon Web Services.

  • According to a 2019 Dice report, there was an 88% year-over-year growth in job postings for data engineers, which was the highest growth rate among all technology jobs.

  • If you are interested in this domain, there cannot be a better time to start learning Azure Synapse Analytics Data Warehouse then now.

Expected Outcomes

In this course

  • You will learn the difference between Traditional vs Modern vs Synapse Data warehouse architecture

  • You will learn why Microsoft Synapse Analytics service is going to be a game-changer in the Data Analytics

  • You will learn how to provision, configure and scale Azure Synapse Analytics service

  • You will learn Cloud Data Warehouse MPP architecture, table types, partitioning, distribution key, and many other important concepts.

  • You will learn different migration techniques and advantage of PolyBase over other techniques with lots of Demos

  • You will learn Security, Configuration, backups, monitoring and other important topics with lots of Demos

  • By the end of this course, you will have a fairly good understanding of Synapse Service and you can directly start working in a Production environment.

  • 100% Syllabus covered for DP200 and DP201 certification exam for Azure Data warehouse (Synapse)

What if I am new in Data Warehouse?

  • I have included a module on Data Warehouse Basics (Crash course to speed up with Cloud warehousing)

Level

  • Beginners & intermediate

Intended Audience

  • Beginners in Azure Platform

  • Data Warehouse developers/ admins

  • Database and BI developers

  • Database Administrators

  • Data Engineers

  • Data Scientist

  • Data Analyst or similar profiles

  • On-Premises Database related profiles who want to learn how to implement these technologies in Azure Cloud.

  • Anyone who is looking forward to starting his career as an Azure Data Engineer.

Prerequisites

  • Basic T-SQL and Database concepts

  • Azure Free trial Subscription

Language

  • English

  • If you are not comfortable in English, please do not take the course, captions are not good enough to understand the course.

What's inside

  • Video lectures, PPTs, Demo Resources, Quiz, Assignment, other important links

  • Full lifetime access with all future updates

  • Certificate of course completion

  • 30-Day Money-Back Guarantee

Course In Detail

Introduction

  • Microsoft has recently released this brand new service, which is a big success for the data team at Microsoft. Synapse contained very rich features, not only to the engine itself to increase performance, but also to add new functionality in providing a unified analytics experience for diff data teams.

  • In the most recent study conducted by GigaOm in January 2019 for the TPC-H benchmark report shows that Synapse Analytics is 14 times fast and still 94% cheaper than any other leading service in the market.

  • And that's why clients are shifting to Azure and Azure is growing at nearly twice the rate of Amazon Web Services. Azure Synapse Analytics truly is a game-changer in Data processing and Analytics.

  • According to a 2019 Dice report, there was an 88% year-over-year growth in job postings for data engineers, which was the highest growth rate among all technology jobs. If you are interested in this domain, there cannot be a better time to start learning Azure Synapse Analytics Data Warehouse then now.

  • I hope you will join me on this exciting journey of learning this technology.

Azure Synapse Analytics Service

  • Why we should consider warehousing solutions in the cloud?

  • And then we'll discuss Microsoft's brand new Azure Synapse analytics service, and how this service brings together enterprise data warehousing and Big Data analytics, and provide a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

  • Advantages of Synapse analytics service over other cloud-based analytics services.

  • We will discuss the difference between Traditional vs Modern vs Synapse Architecture.

  • You will also see Azure Synapse studio which provides a unified experience for all Data Professionals. So, whether you are Data Engineer, Data Scientists, Database administrator, business analysts or any other IT professional, you will find your space in Synapse studio.

  • And then finally in Demo, we'll provision new Azure Synapse Analytics Service, we will see how to pause or resume compute node which is very important, and how to set firewall rules and connect with SQL Server Management studio

Internal and Architecture

  • In this module where you are going to learn Azure Data Warehouse famous MPP or Massive parallel processing architecture.

  • And then we'll discuss various cloud data warehousing internal but important concepts like storage and data distribution through Hash, round-robin and replicated tables

  • We will learn not only different Data types and table types like columnstore, heap and Clustered B-tree index, but we will also learn best practices around, how to partition our data into these diff table types.

  • We will discuss in detail about distribution key and how to analyses the table to find the best distribution key according to partition.

  • Then we'll discuss how to apply these concepts in dimensional modeling.

  • And then finally we'll take a case of Microsoft's famous Adventure works DW, we will download and restore it in our on-premises management studio, and we will analyze the distribution and the data types for Data Warehouse and we will prepare it to migrate to Cloud data warehousing.

Data Migration

  • In this module, we will learn about data loading or data migration in the Azure Data warehouse service

  • We'll start with learning the best practices of loading data in MPP architecture

  • Then we'll learn about different loading methods and we will learn the difference between Single client loading methods and Parallel readers loading methods

  • We will see specifically the difference between SSIS and PolyBase loading methods, and why PolyBase is preferred for large tables.

  • We will learn the PolyBase process in detail and go through all steps to set up the PolyBase environment.

Security

  • In this module, we will take a look at how we can secure our azure SQL data warehouse

  • Actually, without security, nothing else really matters and that's why Microsoft Azure provides 5 layers of defense to secure your Azure SQL Database

  • First is Threat Protection - This is a most outer layer of security, and in this Microsoft Azure constantly monitor the traffic to your Azure SQL Database and look for suspicious patterns.

  • Then the next comes to Network Security - Network security is to make sure only requests which are coming from valid IP addresses can access your database.

  • Authentication and Access control are part of Access Management

    • Authentication - Authentication is about validating your credentials like User Name/User ID and password to verify your identity.

    • And Access control or Authorization determines what kind of access the authenticated user has over particular resources.

  • And finally comes the Data Protection layer - Microsoft provides different information protection and encryption technologies to protect our data in your Azure SQL Database.

Configuration and Optimization

  • In this module, we'll examine configuration settings and common tasks that are available to us inside the Microsoft Azure Synapse Analytics service portal.

  • We will see it is how incredibly easy to backup and restore data warehouse in the Synapse Analytics service portal.

  • Then, we will take a look at price optimization and will see how you evaluate different configuration suits best for your needs.

  • We will learn about Managing workload, which helps solution Architects to ensure that data warehouses always have enough resources to hit SLA for classic data warehousing activities like loading, transforming and querying data.

  • We will learn different monitoring tools like query activity, alerts, metrics, diagnostic settings and resource health provided by Synapse portal. We will also look at the option to submit a support ticket to Microsoft in case you are not able to resolve the issue at your end.

  • And Finally, we are going to delete all the resources we created during Demo, this is very important to avoid any charges when you are not using the system.

Data Warehouse Crash Course

  • In this module, you will learn, what is Data Warehouse, Why we need it and how it is different from the traditional transactional database.

  • We will learn the concept of dimensional modeling which is a database design method optimized for data warehouse solutions.

  • Then I will explain what we mean when we say facts and their corresponding fact tables. What are dimensions and their corresponding dimension tables

  • how are these special kinds of tables joined together to form a star schema or snowflake schema.

  • This section will establish the foundation before you start my course on Azure Synapse Analytics or formally known as Azure SQL Data Warehouse.

Some students Feedback (from other courses)

  • One of the most amazing courses i have ever taken on Udemy. Please don't hesitate to take this course. The instructor is really professional and has a great experience about the subject of the course. - Khadija Badary

  • Very nicely explained most of the concepts. a must have course for beginners - Manoranjan Swain

  • I appreciate this course explaining everything in great detail for a beginner. This will assist me in overcoming challenges at my work - Benjamin Curtis

  • Good course for Beginners. Labs are really helpful to grasp the concept. Thank you - Sapna

Topics touched in this course

Microsoft SQL Server, Azure SQL Server, Azure SQL Data Warehouse, Data Factory, Data Lake, Azure Storage, Azure Synapse Analytics Service, PolyBase, Azure monitoring, Azure Security, Data Warehouse, SSIS

Learn Data Warehousing From Scratch- From Solution Architect

Real life data warehouse guide from the industry expert. Succeed in BI|DataWarehouse|Data Model|BIGDATA.

Created by Asif Raza - DW/BI Solution Architect

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Students: 3764, Price: $89.99

Students: 3764, Price:  Paid

*****

Added Hadoop Distributions Comparison sheet to let you choose the right Hadoop distribution based on several Parameters.

*****

Do you want to master in Data warehousing, keen to become an expert ? Me being worked on several Data Warehousing implementation projects in last 12 years here in UK. I will give you the grain of what's needed to implement a successful Data Warehouse project.

We've heard it all, big data and the intelligence to understand these chunks of data. Most persons have to start from scratch or meet mid-way to become an expert in business Intelligence domain.

Course is meant for someone who wants to understand fundamentals of DW and various architectural pieces around it and eventually become a part of big data revolution.

This course is built to get you the grain of the subject and give you what is essential for newbie to eventually become an expert at the end of the course. Come and Join the journey!!

Course Highlights Introduction

  • Business Challenge?
  • Need for Business Intelligence
  • Define Data warehouse
  • Industry UsingData warehousing
  • Typical BI environment

Data Warehousing Concepts

  • OLTP ,OLAP
  • ODS, Data Marts
  • ETL
  • Facts, Dimensions, SCD
  • Surrogate Keys, Factless-Fact

Two Major school of thoughts

  • Are they at war ?
  • Understand myth
  • Case Studies
  • Ralph Kimball
    • How to design
    • Start Schema, Snow Flake
    • Bus Architecture
    • Sample Data Models
  • Bill Inmon
    • How to design
    • 3rd Normal Form
    • CIF Architecture
    • Sample Data Models

Data Warehouse Appliances

  • Teradata
  • Netezza
  • Exadata

Big Data

  • What's the Buzz word
  • What are 4 V's
  • Understand Big Data in BI terms
  • Major Player
  • What is Hadoop
  • Hadoop in DW world
  • Example - Architecture

NoSQl

  • What it is
  • SQL VS NoSQL
  • Types of NoSQL DB's
  • Major BI Vendors

Wish you all the very best!

ETL Framework for Data Warehouse Environments

The non functional ETL requirements

Created by Sid Inf - Data/ETL Architect

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Students: 3188, Price: $124.99

Students: 3188, Price:  Paid

This course provides a high level approach to implement an ETL framework in any typical Data Warehouse environments. The practical approaches can be used for a new application that needs to design and implement ETL solution which is highly reusable with different data loading strategies, error/exception handling, audit balance and control handling, a bit of job scheduling and the restartability features and also to any existing ETL implementations. For existing implementations this framework needs to be embedded into the existing environment, jobs and business requirements and it might also go to a level of redesigning the whole mapping/mapplets and the workflows (ETL jobs) from scratch, which is definitely a good decision considering the benefits for the environment with high re-usability and improved design standards. 

This course is a combination of standard and practical approaches of designing and implementing a complete ETL solution which details the guidelines, standards, developer/architect checklist and the benefits of the reusable code. And, this course also teaches you the Best practices and standards to be followed in implementing ETL solution. 

Though this course, covers the ETL design principles and solutions based on Informatica 10x, Oracle 11g, these can be incorporated to any of the ETL tools in the market like IBM DataStage, Pentaho, Talend, Ab-intio etc. 

Multiple reusable code bundles from the marketplace, checklists and the material required to get started on UNIX for basic commands and Shell Scripting will be provided. 

An Introduction to Snowflake

Datawarehousing as a Service!

Created by Bhavuk Chawla - Authorized Instructor for Google, Cloudera, Confluent

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Students: 2832, Price: Free

Students: 2832, Price:  Free

Are you also perturbed about Scalability, Performance and Cost of your existing Data Warehouses?

We have a solution for you!

Just keep your gung-ho high and join the live webinar on Snowflake. Snowflake provides Data Warehousing as a Service. It opens the door to numerous benefits including almost Zero maintenance, On Demand Scaling in just a few seconds, Simplifying Data Sharing, Zero Copy Cloning etc.

Agenda:

  1. Evolution of Data Warehousing Technologies

  2. What is Snowflake?

  3. Snowflake vs RedShift

  4. Key Concepts

  5. Snowflake Architecture

  6. Setting up Snowflake Trial Account

  7. Demo

  8. Usecase: Implementing Change Data Capture in Snowflake

Please note that this is not an official course from Snowflake.

You may join our YouTube Channel named "DataCouch" for getting access to interesting videos free of cost.

We have many Google certified instructors who can assist your team in moving forward in Google Cloud implementation in the right way.

We are also an official training delivery partner of Confluent Kafka.. We conduct corporate trainings on various topics including Confluent Kafka Developer, Confluent Kafka Administration, Confluent Kafka Real Time Streaming using KSQL & KStreams and Confluent Kafka Advanced Optimization. Our instructors are well qualified and vetted by Confluent for delivering such courses.

Please feel free to reach out if you have any requirements for Confluent Kafka Training for your team. Happy to assist.

Implementing a Data Warehouse with Microsoft SQL Server

Design and implement a data warehouse

Created by Bluelime Learning Solutions - Learning made simple

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Students: 2139, Price: $94.99

Students: 2139, Price:  Paid

This course describes how to implement a data warehouse solution.
students will learn how to create a data warehouse with Microsoft SQL Server 2014, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Target Audience:

=>This course is intended for database professionals
 who need to create and support a data warehousing solution. Primary responsibilities include:
••Implementing a data warehouse.
••Developing SSIS packages for data extraction, transformation, and loading.
••Enforcing data integrity by using Master Data Services.
••Cleansing data by using Data Quality Services.

Prerequisites :

Experience of working with relational databases, including:
Designing a normalized database.
Creating tables and relationships.
Querying with Transact-SQL.
Some exposure to basic programming constructs (such as looping and branching).
An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.

Students will learn how to :

••Deploy and Configure SSIS packages.
••Download and installing SQL Server 2014
••Download and attaching Adventureworks2014 database
••Download and installing SSDT
••Download and installing Visual studio
••Describe data warehouse concepts and architecture considerations.
••Select an appropriate hardware platform for a data warehouse.
••Design and implement a data warehouse.
••Implement Data Flow in an SSIS Package.
••Implement Control Flow in an SSIS Package.
••Debug and Troubleshoot SSIS packages.
••Implement an ETL solution that supports incremental data extraction.
••Implement an ETL solution that supports incremental data loading.
••Implement data cleansing by using Microsoft Data Quality Services.
••Implement Master Data Services to enforce data integrity.
••Extend SSIS with custom scripts and components.
••Databases vs. Data warehouses
••Choose between star and snowflake design schemas
••Explore source data
••Implement data flow
••Debug an SSIS package
••Extract and load modified data
••Enforce data quality
••Consume data in a data warehouse

Data Warehouse Projects: A Short Course for IT Executives

Learn how to be successful with data warehouse projects.

Created by Bob Wakefield - Data Management Expert

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Students: 2059, Price: Free

Students: 2059, Price:  Free

2nd Edition now available!

Data warehouse projects can be expensive and complex. If an organization does not currently have a data warehouse, the value of building one may not be clear. This course will teach you how to manage a data warehouse project in a timely, cost-effective manner that is on budget and will demonstrate value to the business from day one.

This course is designed for people who manage IT projects. If you are not an IT manager but are interested in learning how to build a data warehouse, this course can serve as a solid introduction to data warehousing.

You will learn how to manage the people and processes necessary to bring an enterprise data warehouse to initial operating capability. You will be taught common data warehouse terms so you can effectively communicate with technical resources. You will be introduced to the documents necessary to design and build a data warehouse. You will gain knowledge about common pitfalls to avoid. You will learn who you need to hire to work on the project and how to select those people.

Updates in the 2nd edition include:

Links to external resources have been added to the relevant lectures.

New lectures added after the initial publish date have been fully integrated.

Entire class has been re-recorded using professional voice talent.

A Python project with coding framework and unit testing

Real world python coding framework and unit testing - logging, error handling, config , database, PyTest , REST API

Created by FutureX Skill - Big Data, Cloud and AI Solution Architects

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Students: 1480, Price: Free

Students: 1480, Price:  Free

Learn how to code and unit test Python applications in a real world project. Go beyond the basics by solving a practical use case step by step. This course is designed for Python beginners who want to transition for academic background to a real world developer role !

Course Project :

You will be building a Python application to read data from files and store the data into PostgreSQL database. You will be creating REST endpoints using which external users will interact with your application data. All the industry standard best practices in terms of logging, error handling, config file, code structuring will be used in the application.

Course structure :

  • Python (3.9) and PyCharm IDE installation

  • Python basics - Get started with basic Python data types including List, Tuple and Dictionary

  • Organizing code with Classes and Modules - Understand core concepts of classes and packages

  • Python logging - Implement logging using basic config and file config

  • Python error handling - Learn how to handle exceptions.

  • Python PostgreSQL database interaction - Understand how to read and write to PostgreSQL using psycopg2

  • Create REST API using Python - Learn to create APIs using Python Flask framework

  • Reading configuration from property file - Learn how to avoid hardcoding of configurable properties

  • Unit testing - Learn to test your application using unittest package

  • Unit testing - Learn to test your application using PyTest package

You will learn the above concepts by building a real world file processing application. No prior Python knowledge required.

Prerequisites :

  • Basic programming skills

  • Basic knowledge of SQL queries

Data Warehousing and Business Intelligence for Managers

Manage Data Warehousing and Business Intelligence Developers and Projects

Created by Samori Augusto - Data Analytics Consultant, Microentrepreneur, PMP, & PMI-ACP

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Students: 1181, Price: $39.99

Students: 1181, Price:  Paid

Data Warehousing and Business Intelligence for Managers prepares you for the many data warehousing projects that are underway or scheduled to begin in large or small organizations. It's also an entryway into Big Data. If you've heard of data warehousing but never knew what it meant, this is the course for you. Have you always wanted to know what kind of enterprise software is made by Oracle, SAP, Informatica, Tableau, SAS, and even Microsoft?  The answer is Data Warehousing and Business Intelligence software, two categories of software that can even include one thing you probably have on your latptop right now: Microsoft Excel. 

The course is geared towards managers, but is also effective for non-techies or novices who want to understand one of the most important approaches to managing operations that organizations undertake, and that affects your life and your interaction with technology every day. The course is a series of video presentations, but also includes quizzes, a final project, and PDF downloads that will help familiarize you with data warehousing. 

Recent additions to this course include a greater exploration of Big Data, Data Lakes, and a little about cloud Big Data architecture. The course will continue to grow to explore more about the crossover and intersections between Data Warehousing, Business Intelligence, and Big Data (aka Analytics).

This course is quick to complete, giving you an overview of what you need most without going too deep for Data Warehousing novices. If you want a solid introduction to Data Warehousing and Business Intelligence, sign up for this course today!

3 hours of material

New material added periodically to the course

LIFETIME ACCESS to the course

Learn Data Warehousing and Analysis with Microsoft BI Tools

Learn how extract, clean and load data in a database using Microsoft Excel and Business Intelligence tools

Created by Data Science Guide - Data Scientist & SQL Developer

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Students: 1156, Price: $19.99

Students: 1156, Price:  Paid

Learning how to extract, clean and load data into a SQL database warehouse are highly required skills for data analysis field. You will learn in this course how to use Microsoft Excel to clean your data before loading them into a Microsoft SQL Server database. You will learn how to use SQL Server Integration Services (SSIS) which is one of Microsoft Business Intelligence tools to perform ETL process. You will learn a simple technique that save you a lot of time and help to avoid many possible errors during the ETL process. You will learn also how to use SQL Server Reporting Services (SSRS) to create business reports and  data analysis with SQL queries. This course is designed to be more practical by putting your hands on real projects with diverse business scenarios to learn by practice.  Learning via practice is the best way to get knowledge stuck in your mind because it is similar to acquire experience through work. 

Data Warehouse ETL Testing & Data Quality Management A-Z

ETL Testing and Data Quality Management for beginners with practical exercises and certificate of completion.

Created by Lorenz DS - BI Consultant | Data Engineer

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Students: 759, Price: $19.99

Students: 759, Price:  Paid

Learn the essentials of ETL Data Warehouse Testing and Data Quality Management through this step-by-step tutorial. This course takes you through the basics of ETL testing, frequently used Data Quality queries, reporting and monitoring. In this tutorial we will learn how to build database views for Data Quality monitoring and build Data Quality visualizations and reports!

..Learn to build data quality dashboards from scratch!

..Learn some of the most common mistakes made when performing ETL/ELT tests..

..Forget about manual ad-hoc ETL testing, learn more about automated ETL and data quality reports

The course contains training materials, where you can practice, apply your knowledge and build an app from scratch. The training materials are provided in an Excel file that you can download to your computer. Each module also ends with a short quiz and there is a final quiz at the end of the course.

After completion of this course, you will receive a certificate of completion.

Good luck and hope you enjoy the course.

Pre-requisites:

  • Basic knowledge of SQL

  • Some experience with Visualization tools would be helpful, but not required

  • Basic setup of database (PostgreSQL, Oracle) and visualization tool (Qliksense) is recommended

Course content:

The course consists of the following modules:

  • Introduction

  • What is ETL/ELT Testing and Data Quality Management?

  • Build database views for Data Quality Monitoring

  • Build dashboards for Reporting

  • Exercises

  • Final Quiz

Who should follow this course?

  • Students that want to learn the basics of ETL/ELT testing and Data Quality Management

  • Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples

  • Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards

  • Data Stewards and Managers considering to apply data quality standards within their organization

Cloud Data Warehouse Concepts

The beginner's guide to Cloud Data Warehouse

Created by Sid Inf - Data/ETL Architect

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Students: 416, Price: $94.99

Students: 416, Price:  Paid

‘The Cloud’ or ‘Cloud computing’ is one of the hottest buzzwords in technology. It appears more than 48 million times on the Internet search every day. Cloud computing and software-as-a-service (SaaS) have been around for quite some time now and we have been using it via multiple applications both at work and personally via mobile apps.

But when it comes to the data warehouse on a cloud, the concept or the idea has recently emerged as an alternative to conventional or traditional, on-premises data warehousing and similar types of solutions which we have been working on.

When choosing a DW solution for the first time, the very first consideration is typically one between an on-prem DW or a cloud-based one. And while a lot of folks new to the Data Warehouse domain go straight to the cloud these days because it is faster, easier and pay as you go or use method of pricing, the scalable features and the quick turnaround time on multiple aspects. Not that the Cloud is one stop solution for all Data Warehouse needs and there are still many reasons why an organization might want to choose an on-prem solution.

Even now there are a lot of projects/implementations which are maintaining and enhancing the traditional data warehouses on a daily basis. And, lot of projects and team members are also dealing with issues with different kinds of sources, the increase in volumes of data and the outburst of new requirements from business and analytics to see the real value of the unstructured formats of data.

I’m here to help you on your journey to understand the basics of ‘Cloud’ and the Cloud Data Warehouse. We would take little baby steps and go slow and easy, so you can learn more about what the cloud Data Warehouse really is and make sure that you’ll understand the cloud Data Warehouse by the time you finish with this course.

We will take examples of our day to day use of applications like Facebook, Netflix, Google Maps etc to learn more and understand better.

Data Warehousing and SQL End to End

Become an expert at SQL and learn SQL end to end, clear all your concepts of SQL in depth and become SQL expert

Created by Rahul Tiwari - Its all about data

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Students: 265, Price: $89.99

Students: 265, Price:  Paid

You'll learn how to read and write complex queries to a database using one of the most in-demand skills - Oracle SQL. These skills are also applicable to any other major SQL database, such as MySQL, Microsoft SQL Server, Amazon Redshift, PostgreSQL, and much more.

Learning SQL is one of the fastest ways to improve your career prospects as it is one of the most in-demand tech skills! In this course, you'll learn quickly and receive challenges and tests along the way to improve your understanding!

In this course, you will learn everything you need to become a SQL expert! Including:

  • Get started with SQL

  • Learn the basics of SQL syntax

  • Analyzing data using aggregate functions with GROUP BY commands

  • Running advanced queries with string operations and comparison operations

  • Set Operators

  • Subqueries, correlated subqueries

  • Learn to use logical operators to add logic flow to your SQL queries

  • Learn common SQL JOIN commands

  • Learn to create tables and databases with constraints on data entries

  • and much, much more!

  • What is a data warehouse?

  • What is the need for a data warehouse?

  • What is the difference between a data warehouse and a data lake?

  • Bottom-up and top-down approach of data warehousing project.

  • OLTP and OLAP transactions

SQL is one of the most in-demand skills for business analysts, data scientists, and anyone who finds themselves working with data! Upgrade your skillset quickly and add SQL to your resume by joining today!

All the very best!!!

Modeling Data Warehouse with Data Vault for Beginners

Course covers the basics and fundamentals of Data Vault 2.0 along with Agile Methodology and Big Data

Created by Esra Ekiz - Product Owner & Analytic Consultant

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Students: 79, Price: $44.99

Students: 79, Price:  Paid

Data Vault is an innovative modeling technique invented by Dan Linstedt to simplify data integration from multiple sources, offers auditability and design flexibility to cope with data from the heterogeneous information systems which supports most business demands today

It is designed to deliver an Enterprise Data Warehouse while solving many of the drawbacks of the 3NF (Inmon) and Dimensional Modelling(Kimball).

In this course, you will

  • Learn the basics of Data Modelling to become familiar with core concepts

  • Understand the fundamentals of traditional Data Warehouse approaches

  • Learn many of today’s Data Warehousing problems and issues with 3NF or Star Schema

  • Understand how Data Vault addresses these challenges and provide an innovative approach

  • Learn the fundamentals of the Data Vault modeling approach from core concepts to advanced, and from architecture to key benefits

  • Learn how to effectively model Hubs, Links and Satellites

  • Understand DV Modeling constructs in detail

  • Understand the different architectural and modeling layers of DV 2.0

  • Learn Business Vault, Information Vault and significance of Dimensional Layer

  • Understand where to use 3NF, Dimensional Model or Data Vault

  • Understand loading patterns and architecture

  • Learn  how to handle schema and grain changes on the Data Vault model

  • Learn why Agile Methodology is important for scalable Data Warehouses

  • Get familiar with Big Data Terminologies along with Data Vault Methodology

  • It also contains a hands-on case study to get participants familiar with the principles and concepts