Learn Data Warehousing In 24 Hours
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Learn Data Warehousing in 24 Hours
Unlike popular belief, Data Warehouse is not a single tool but a collection of software tools. A data warehouse will collect data from diverse sources into a single database. Using Business Intelligence tools, meaningful insights are drawn from this data. The best thing about “Learn Data Warehousing in 1 Day" is that it is small and can be completed in a day. With this e-book, you will be enough knowledge to contribute and participate in a Data warehouse implementation project. The book covers upcoming and promising technologies like Data Lakes, Data Mart, ELT (Extract Load Transform) amongst others. Following are detailed topics included in the book Table Of Content Chapter 1: What Is Data Warehouse? 1. What is Data Warehouse? 2. Types of Data Warehouse 3. Who needs Data warehouse? 4. Why We Need Data Warehouse? 5. Data Warehouse Tools Chapter 2: Data Warehouse Architecture 1. Characteristics of Data warehouse 2. Data Warehouse Architectures 3. Datawarehouse Components 4. Query Tools Chapter 3: ETL Process 1. What is ETL? 2. Why do you need ETL? 3. ETL Process 4. ETL tools Chapter 4: ETL Vs ELT 1. What is ETL? 2. Difference between ETL vs. ELT Chapter 5: Data Modeling 1. What is Data Modelling? 2. Types of Data Models 3. Characteristics of a physical data model Chapter 6: OLAP 1. What is Online Analytical Processing? 2. Types of OLAP systems 3. Advantages and Disadvantages of OLAP Chapter 7: Multidimensional Olap (MOLAP) 1. What is MOLAP? 2. MOLAP Architecture 3. MOLAP Tools Chapter 8: OLAP Vs OLTP 1. What is the meaning of OLAP? 2. What is the meaning of OLTP? 3. Difference between OLTP and OLAP Chapter 9: Dimensional Modeling 1. What is Dimensional Model? 2. Elements of Dimensional Data Model 3. Attributes 4. Difference between Dimension table vs. Fact table 5. Steps of Dimensional Modelling 6. Rules for Dimensional Modelling Chapter 10: Star and SnowFlake Schema 1. What is Multidimensional schemas? 2. What is a Star Schema? 3. What is a Snowflake Schema? 4. Difference between Start Schema and Snowflake Chapter 11: Data Mart 1. What is Data Mart? 2. Type of Data Mart 3. Steps in Implementing a Datamart Chapter 12: Data Mart Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Mart? 3. Differences between a Data Warehouse and a Data Mart Chapter 13: Data Lake 1. What is Data Lake? 2. Data Lake Architecture 3. Key Data Lake Concepts 4. Maturity stages of Data Lake Chapter 14: Data Lake Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Lake? 3. Key Difference between the Data Lake and Data Warehouse Chapter 15: What Is Business Intelligence? 1. What is Business Intelligence 2. Why is BI important? 3. How Business Intelligence systems are implemented? 4. Four types of BI users Chapter 16: Data Mining 1. What is Data Mining? 2. Types of Data 3. Data Mining Process 4. Modelling 5. Data Mining Techniques Chapter 17: Data Warehousing Vs Data Mining 1. What is Data warehouse? 2. What Is Data Mining? 3. Difference between Data mining and Data Warehousing?
100 Puzzles to Learn Data Warehousing
Learning how to design a data warehouse may be difficult. Ralph Kimball has some great legacy books on the dimensional modeling techniques, but they are verbose, with complicated examples. Our illustrated examples here are kept simple on purpose, to help you better understand complicated concepts like periodic snapshot fact tables, degenerate dimensions, late arriving facts or dimensions. We focus our puzzles on Ralph Kimball's dimensional modeling techniques, but we also introduce you to Extract-Transform-Load (ETL) basics, OLAP fundamentals and some other important things you must know about data warehouses in general. We dive deep into slowly changing dimensions (SCD), with other illustrated examples to help you get the ideas in no time. You need just some basic prior knowledge about Data Warehouses in general. The explanations and external references from the answers to our questions will help you learn the rest. We also assume you already have some basic background in data modeling for relational databases, and SQL. These puzzles are for Software Developers and Engineers, Database Engineers and Architects, or Data Analysts. Difficulty level is from beginner to advanced. We've split the 100 questions into 5 quizzes with 20 single and multi-choice questions each. Try solving each quiz separately, writing down on a piece of paper the answer to each question. Then go to the Answers and Explanations section, and learn more from our solutions to the puzzles. Follow the links to external references for a deep dive on the subject. An interactive version of this book has been implemented on Udemy as 100 Puzzles to Learn Data Warehousing.
Learn SAP BI in 24 Hours
SAP Business Intelligence (BI) is a tool to analyze raw data and derive meaning inferences. SAP BI gives single point access to data from various sources. Robust reports and visualization are available to analyze the data. SAP BI can analyze multidimensional data, easily integrates with other applications and has a mobile app. Here is what is covered in the book - Table Of Content Chapter 1: Introduction SAP BI Chapter 2: Overview of SAP BI Architecture Chapter 3: All About Infoobject Infoarea & Infoobject Catalog Chapter 4: How To create an INFOAREA Chapter 5: How to create an INFOOBJECT CATALOG Chapter 6: How To Create an INFOOBJECT with Characteristics Chapter 7: How to Create INFOOBJECTS with Key Figures Chapter 8: What is DSO? Why Use It? Chapter 9: What is Standard DSO? How To Create One? Chapter 10: What is Write Optimized DSO? How To Create One? Chapter 11: What is Direct Update DSO? How To Create One? Chapter 12: What is InfoSet? Chapter 13: What is an Infocube? How To Create One? Chapter 14: How to Load Master Data from Flat File? Chapter 15: How To Load Transaction Data From Flat File? Chapter 16: How to load Master Data from ECC? Chapter 17: How To Load Transaction Data From ECC? Chapter 18: All About Classical & Extended Star Schema Chapter 19: All About Process Chains in SAP BI/BW Chapter 20: Installing BW Standard Content Chapter 21: Introduction to BEX Query Designer and Query Elements Chapter 22: Learn About Key & Characteristics Settings CFK, RFK & Formulas Chapter 23: SAP BW / BI Interview Questions & Answers