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E-grāmata: Business Intelligence Tools for Small Companies: A Guide to Free and Low-Cost Solutions

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  • Formāts: EPUB+DRM
  • Izdošanas datums: 25-May-2017
  • Izdevniecība: APress
  • Valoda: eng
  • ISBN-13: 9781484225684
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Business Intelligence Tools for Small Companies: A Guide to Free and Low-Cost SolutionsPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 25-May-2017
  • Izdevniecība: APress
  • Valoda: eng
  • ISBN-13: 9781484225684
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Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies.

Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database.

The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. 

What You'll Learn

You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to:

  • Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure
  • Extract data from any enterprise resource planning (ERP) tool
  • Process and integrate BI data using open-source extract-transform-load (ETL) tools
  • Query, report, and analyze BI data using open-source visualization and dashboard tools
  • Use a MOLAP tool to define next year's budget, integrating real data with target scenarios
  • Deploy BI solutions and big data experiments inexpensively on cloud platforms

Who This Book Is For

Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions
About the Authors xvii
About the Technical Reviewer xix
Acknowledgments xxi
Introduction xxiii
Chapter 1 Business Intelligence for Everybody
1(28)
What Is Business Intelligence?
2(3)
BI Evolution
3(2)
BI Characteristics
5(3)
Hidden Relevant Information
5(1)
Accuracy
6(1)
Significant KPIs
6(1)
On Time
6(1)
Company Analytics Life Cycle and Continuous Improvement
7(1)
Benefits of BI
8(3)
Direct Benefits
8(1)
Indirect Benefits
9(1)
Objectives
10(1)
Who Can Get Benefit from BI?
11(1)
BI Platform Components
11(2)
Source ERP
12(1)
Database
12(1)
ETL
13(1)
Front-End Tool
13(1)
Budgeting Tool
13(1)
BI Platform Location
13(1)
BI Concepts
14(7)
Datawarehouse
14(1)
DataMart
15(1)
Logical Model
16(3)
Physical Model
19(1)
BI Main Objects
20(1)
BI Approaches
21(3)
Query and Reporting
21(1)
Information Sharing
22(1)
Dashboarding
22(1)
Data Import
22(1)
Data Discovery
22(1)
MOLAP
23(1)
Data Mining
23(1)
Incoming Approaches
24(1)
BI Capabilities
24(4)
Drilling
24(1)
Pivoting
25(1)
Visualizations
25(1)
Sorting
26(1)
Grouping
26(1)
Filtering
26(1)
Conditional Expressions
27(1)
Subtotals
27(1)
Administration
28(1)
User Interface
28(1)
Conclusion
28(1)
Chapter 2 Agile Methodologies for BI Projects
29(28)
Introduction to Agile Methodologies
30(1)
Agile Approaches
31(15)
Our Recommended Mix between Scrum and Kanban
31(1)
Developing Projects with Scrum
32(11)
Maintenance with Kanban
43(2)
Mix of Both Methodologies, Scrumban
45(1)
Peculiarities of Scrum for BI
46(6)
Sprint 0 - Longer Initial Analysis
46(2)
BI Project Segmentation
48(1)
Front-End vs. Back-End Activities
49(1)
Role Isolation - Specific Knowledge
50(1)
Developer Story Types in BI
51(1)
Agile Management Tools
52(4)
Trello
53(1)
JIRA Software
54(2)
Conclusion
56(1)
Chapter 3 SQL Basics
57(36)
What Is SQL?
57(1)
The Relational Model
58(2)
Databases and Database Vendors
60(32)
ACID Compliance
61(1)
Types of SQL Statements
62(1)
SQL Datatypes
63(1)
Retrieving Data from a Table
63(4)
Sorting
67(2)
Filtering
69(2)
Grouping Data
71(3)
Using Subqueries
74(3)
Joining Tables
77(8)
Set Operations
85(4)
Working with Dates
89(2)
Conditional Expressions
91(1)
Conclusion
92(1)
Chapter 4 Project Initialization -- Database and Source ERP Installation
93(24)
The Need for Data
93(1)
Setting the System Up with Odoo ERP
93(18)
The Bitnami Odoo Package
94(1)
Downloading and Installing Odoo
95(1)
Bitnami and Odoo Configuration Files
96(1)
Installing psql and Checking the Database Connection
97(1)
Accessing the Application
98(1)
Configuring and Installing Modules
99(2)
Selecting our Datawarehouse Database
101(1)
Sourcing and Installing MariaDB
102(5)
Creating Our First Database
107(4)
Analyzing the Data Source
111(1)
Inspecting our Model
111(2)
Setting up a PostgreSQL Connection to the Server
113(3)
Conclusion
116(1)
Chapter 5 Data Modeling for BI Solutions
117(30)
Naming Convention and Nomenclature
117(2)
Modeling Steps
119(5)
Business Model
119(1)
Logical Model
120(1)
Dimensional Model
121(1)
Physical Model
122(2)
Defining our Model
124(4)
Sales Dimension
125(2)
Status Table
127(1)
Currency Dimension
127(1)
Customer Dimension
127(1)
Employee Dimension
127(1)
Product Dimension
128(1)
Time Dimension
128(1)
Exploring Data Modeling Possibilities
128(9)
View Layer
129(1)
Data Split
130(1)
Fact Normalization and Denormalization
131(1)
Time Transformations
132(1)
Fact Phases
133(1)
Real vs. Potential
133(1)
Historical Hierarchies
134(1)
Multiple Views Using a Table, Entity Isolation
134(1)
Modifying Existing Structures, Adding More Sales Document Status
135(1)
Currency Transformation
135(2)
Geographical Information
137(1)
Data Modeling Tools
137(7)
Erwin DataModeler
137(5)
MySQL Workbench
142(2)
Preparing the ETL
144(2)
Source Systems
144(1)
Source Tables
145(1)
Source Fields
145(1)
Conclusion
146(1)
Chapter 6 ETL Basics
147(38)
Why Do We Need an ETL Process?
147(1)
Details of the Solution
147(1)
Open Source ETL Suites
148(1)
Downloading and Installing Pentaho Data Integration
148(2)
Understanding ETL Concepts
150(33)
Repositories and Connections
150(4)
Transformations, the Core of Kettle
154(1)
Jobs or How to Organize a Set of Transformations in a Workflow
155(1)
Create and Share a Connection
156(1)
The Global Picture
157(1)
The Product, Product Category, and Product Parent Category Tables
157(2)
The Customer and Customer Country Tables
159(1)
The Employee and Employee Category and Employee Department Tables
160(1)
The Fact Table: How to Create the Transformation for the Sales
160(2)
Creating the Time Dimension
162(14)
Connecting Allot It Up
176(6)
Designing the Job
182(1)
Open Source Alternatives to PDI
182(1)
Conclusion
183(2)
Chapter 7 Performance Improvements
185(22)
Database Optimizations
185(16)
Avoid Using Dates for Join Keys (and Primary Keys Too)
185(1)
Analyze the Tables in Your Database
186(1)
Indexing, or How to Speed Up Queries
187(4)
Partitioning
191(6)
Using the EXPLAIN Sentence
197(2)
Views and Materialized Views
199(1)
HINTS
200(1)
Denormalization
201(1)
Disabling Triggers and Constraints
201(1)
ETL Optimizations
201(4)
Offloading Operations to the Database
201(1)
Check the Network Links
201(1)
Performance Tips with PDI
202(3)
Conclusion
205(2)
Chapter 8 The BI Reporting Interface
207(28)
How to Choose the BI Tool
207(1)
Best Practices in Dashboarding
208(8)
Starting from Top Left
209(1)
Joining Related Information
209(1)
Focus on Relevant Data
210(1)
Formatting Recommendations
210(2)
Graphic Usages
212(4)
BI Tools
216(17)
Microstrategy Desktop
216(7)
Microsoft Power BI
223(5)
Qlik Sense
228(5)
Conclusion
233(2)
Chapter 9 MOLAP Tools for Budgeting
235(20)
Multidimensional Databases
236(5)
Dimensions or Axes for Analysis
237(2)
Dimension Members
239(2)
Sharing Properties across Cubes
241(1)
MDX Language
241(1)
MOLAP Data Interfaces
242(2)
Data Import
243(1)
Source Data Preparation
243(1)
Data Export
244(1)
Calculations
244(1)
PowerOLAP
245(7)
Starting with PowerOLAP
245(2)
Creating Dimensions in PowerOLAP
247(1)
Cube Definition
248(1)
Slices
249(1)
Formulas
250(1)
Caching
251(1)
Data Import and Export
251(1)
Conclusion
252(3)
Chapter 10 BI Process Scheduling: How to Orchestrate and Update Running Processes
255(18)
Finishing the ETL
255(6)
Creating the Job in PDI
255(6)
Overview at PDI Command-Line Tools
261(3)
Launching Transformations from the Command Line with Pan
261(2)
Launching Jobs from the Command Line with Kitchen
263(1)
Scheduling Jobs in the Task Scheduler
264(3)
Scheduling a PDI Job in Windows
264(1)
Scheduling a PDI Job in Unix/Linux
265(2)
Running Database Maintenance Tasks
267(4)
Backing Up Our MySQL/Maria DB Database
267(1)
Perform Checks and Optimizations in the Database
268(3)
Conclusion
271(2)
Chapter 11 Moving to a Production Environment
273(22)
Multienvironment Scenario
273(8)
Deploying a Productive Environment
274(4)
Adding Environments
278(1)
Isolation of Environments
279(1)
Multienvironment Recommendations
279(2)
Maintaining Your Environment
281(8)
Object Life Cycle
281(3)
Monitoring Tools
284(1)
High Availability
285(1)
Using Testing as Disaster Recovery of Production
286(1)
Backing Up Your Platform
287(1)
Historification Process
288(1)
Security
289(3)
Security Management, Using Roles and Groups
290(1)
User Role Definition
291(1)
Security Matrix
291(1)
Auditing
292(2)
Security Audits
292(1)
Auditing Best Practices
293(1)
Conclusion
294(1)
Chapter 12 Moving BI Processes to the Cloud
295(20)
Deciding our Cloud Provider
295(4)
Initial Considerations
295(3)
A First Look at the Physical Design
298(1)
Choosing the Right Cloud Provider
299(15)
Amazon Web Services (AWS)
299(12)
Microsoft Azure
311(2)
Google Cloud
313(1)
Vendor-Based Cloud Solutions
314(1)
Conclusion
314(1)
Chapter 13 Conclusions and Next Steps
315(4)
Documentation
315(1)
BPM Software
316(1)
Big Data
317(2)
Index 319
Albert Nogués is BI Project Manager/BI Architect/BI Developer for Technology2Client, a consultancy to the BI and DWH teams at Danone. He also manages BI projects for Betvictor, a sports gaming company, and designs APIs and interfaces for market pricing services and traders. He has deep knowledge of the full BI stack and holds Oracle certifications in OCA, OCP, and Performance Tuning. Albert received multiple MS degrees in Computer Science and ICT from the Universitat de Catalunya and Universitat Oberta de Catalunya. Juan Valladares is the founder and CEO of Best in BI Solutions, a business intelligence consultancy whose clients include T2C, everis, and other consulting companies. Juan collaborates with end customers such as Zurich, Danone, or Mondelez. A telecommunications engineer by training, Juan has 15 years of experience in business intelligence, data modeling, and BI system administration. He is specialized and certified in Microstrategy. He teaches courses in BI tools, high-concurrency platform management, and ETL and BI processes development. He received his MBA from the Universidad de la Rioja and his engineering degree in telecommunications from the Universitat Politčcnica de Catalunya.
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