SlideShare a Scribd company logo
www.edureka.co/data-warehousing-and-bi
Mastering In DataWarehousing & Business Intelligence
Slide 2 www.edureka.co/data-warehousing-and-bi
At the end of this module, you will be able to Know :
Objective
 What is Data Warehousing & Business Intelligence ?
 What is Data Warehousing Architecture ?
 What is Data Modelling / Introduction to ER Win r9 Tool ?
 What is ETL / An Open Source ETL Tool – Talend 5.x ?
 What is Business Intelligence / An Open Source Tableau Public 9.x ?
Slide 3Slide 3Slide 3 www.edureka.co/data-warehousing-and-bi
What is Data Warehouse
A data warehouse refers to a database that is maintained
separately from an organization’s operational database
“A data warehouse is a subject-oriented, integrated, time-
variant, and nonvolatile collection of data in support of
management’s decision-making process.”
Loosely Speaking
Officially Speaking
W.H. Inmon
Slide 4Slide 4Slide 4 www.edureka.co/data-warehousing-and-bi
Subject Oriented
Data Warehouse Properties
Non Volatile
Integrated
Time Variant
Data Warehousing
Slide 5Slide 5Slide 5 www.edureka.co/data-warehousing-and-bi
Subject-Oriented
Data is categorized and stored by business subject rather than by application
Equity
Plans
Shares
Customer
financial
information
Savings
Insurance
Loans
OLTP Applications Data Warehouse Subject
Slide 6Slide 6Slide 6 www.edureka.co/data-warehousing-and-bi
Integrated
OLTP Applications
Savings
Current
accounts
Loans
Data Warehouse
Data on a given subject is defined and stored once.
Customer
Slide 7Slide 7Slide 7 www.edureka.co/data-warehousing-and-bi
Time-Variant
Data is stored as a series of snapshots, each representing a period of time…
TIME DATA
Jan-97 January
Feb-97 February
Mar-97 March
Jan-97 January
Slide 8Slide 8Slide 8 www.edureka.co/data-warehousing-and-bi
Non-Volatile
Typically data in the data warehouse is not updated or deleted.
Insert Update Delete Read Read
Operational Warehouse
Load
Slide 9Slide 9Slide 9 www.edureka.co/data-warehousing-and-bi
Changing Data
Warehouse Database
First time load
Refresh
Refresh
Operational Database
Slide 10Slide 10Slide 10 www.edureka.co/data-warehousing-and-bi
What is Data Warehouse
“Data warehouse is the conglomerate of all data marts
within the enterprise. Information is always stored in the
dimensional model.”
Officially Speaking
Ralph Kimball
Slide 11Slide 11Slide 11 www.edureka.co/data-warehousing-and-bi
InmonVsRalphKimball
Characteristics Inmon Kimball
Business Decision Support
Requirements Strategic Tactical
Data Integration Requirement Enterprise Wise Integrator Individual Business Requirement
Data Structure Requirement
Data that meet multiple and varied
information needs and non-metric data
KPI, Business Performance Measure &
Scorecards Requirements
Persistency of Data in Source System Source Systems have high rate of
change
Source Systems are quite stable
Skill Sets Bigger Team of Specialists Small Team of Generalists
Time Constraint Longer Time Required Urgent delivery as this is subjective
Cost to Build High Start-up Costs Low Start-Up Costs
Slide 12Slide 12Slide 12 www.edureka.co/data-warehousing-and-bi
Data Ware Housing Products
Entity Relationship / Schema Modeling
Data Integration / ETL
Slide 13Slide 13Slide 13 www.edureka.co/data-warehousing-and-bi
What is Business Intelligence?
Business intelligence (BI) is the set of techniques and tools for the transformation of raw / production and
operational data into meaningful and useful information for business analysis purposes for various level.
Business intelligence (BI) talks about how traditional data which transform into the BI which have multiple
initiatives to measure, manage, and improve on the performance of individuals, processes, teams, and business
units for the specific business area.
During the operation of business, the following questions must be asked. The functions of monitoring,
analyzing, and planning delve into these questions as follows :
• What has happened?
• What is happening?
• Why?
• What will happen?
• What do we want to have happen?
Slide 14Slide 14Slide 14 www.edureka.co/data-warehousing-and-bi
What is Business Intelligence Categories?
Strategic Business Intelligence: Management collaborates and agrees on a strategy and a method in which they
would like to see information presented, for example, in maps, scorecards, reports, or dashboards.
Now that you have your strategy defined, it is imperative that you do something with the data that you have collected
Analytical Business Intelligence: Once Strategic BI sets the foundation in the form of key performance metrics,
then Analytical BI is employed to identify the source of an issue once it has been uncovered.
Tools like analytic dashboards, OLAP, predictive analytics, and ad hoc queries are utilized to determine the location or
the cause of a major problem.
Slide 15 www.edureka.co/data-warehousing-and-bi
Data Ware House Architecture
Slide 16Slide 16Slide 16 www.edureka.co/data-warehousing-and-bi
- CA ERwin Introduction
• ERwin is a popular data modeling
tool used by a number of major
companies throughout the world.
The product is currently owned,
developed, and marketed by
Computer Associates, a leading
software company.
• The product supports a variety of
aspects of database design,
including data modeling, forward
engineering (the creation of a
database schema and physical
database on the basis of a data
model), and reverse engineering
(the creation of a data model on the
basis of an existing database) for a
wide variety of relational DBMS,
including Microsoft Access, Oracle,
DB2, Sybase, and others.
Slide 17Slide 17Slide 17 www.edureka.co/data-warehousing-and-bi
Physical ER Diagram
Slide 18Slide 18Slide 18 www.edureka.co/data-warehousing-and-bi
Open Source VS Commercial ETL Tools
Open Source ETL Commercial ETL
License Details
Licensing Model Open-Core Model. No charges for extra
CPU cycles
Core Model. Extra usage charges can be
applied for over-the-limit CPU cycles
Licensing Channel via GNU public license/Apache license Vendor specific
Cost Differentiation
License Costs 30-60% < 1X times Commercial license
(Mostly)
1X times
Support and Maintenance Costs Close to Commercial vendor costs
(Mostly)
Close to Open-Source
Advanced Features Offered through "Commercial" Open-
Source
Add-ons
Type of Support and Maintenance Tiered pricing model. E.g.
Community(Free, Forums), Silver, Gold
and Platinum Editions
Not offered in tiers (Mostly). Add-on to
licensing costs
Slide 19Slide 19Slide 19 www.edureka.co/data-warehousing-and-bi
Talend Open DI Studio 5.x - Overview
• Talend Open Studio for Data Integration operates as a code generator, producing data-transformation scripts and
underlying programs in Java. Its GUI gives access to a metadata repository and to a graphical designer. The
metadata repository contains the definitions and configuration for each job - but not the actual data being
transformed or moved. All of the components of Talend Open Studio for Data Integration use the information in
the metadata repository.
• The product is based on Eclipse.
• Talend Open DI Studio typically use for:
• synchronization or replication of databases
• right-time or batch exchanges of data
• ETL (Extract/Transform/Load) for analytics
• data migration
• complex data transformation and loading
• data quality exercises
• big data
• Talend Open Studio for Data Integration primarily differs from Talend Enterprise Data Integration in that the
Enterprise version has a Subversion plug-in built in, as well as support for joblets. Using Talend Enterprise Data
Integration, ETL and ELT jobs can have a dynamic schema.
Slide 20Slide 20Slide 20 www.edureka.co/data-warehousing-and-bi
Talend - History
Slide 21Slide 21Slide 21 www.edureka.co/data-warehousing-and-bi
Talend - Partners
Slide 22Slide 22Slide 22 www.edureka.co/data-warehousing-and-bi
Talend - Customers
Slide 23Slide 23Slide 23 www.edureka.co/data-warehousing-and-bi
Talend - Market Position
Slide 24Slide 24Slide 24 www.edureka.co/data-warehousing-and-bi
Talend - Product Offering
Slide 25Slide 25Slide 25 www.edureka.co/data-warehousing-and-bi
Talend DI Studio - Welcome Page
Slide 26Slide 26Slide 26 www.edureka.co/data-warehousing-and-bi
Data visualization With Tableau
• Data visualization tools allow anyone to organize and
present information intuitively. This is becoming more
vital as data proliferates in every field from bar codes
in retail stores to player behavior in online games.
• All of this data is meaningless without a way to
organize and present important findings within it.
People comprehend data better through pictures than
by reading numbers in rows and columns.
• So by visualizing data, you are able to more effectively
ask and answer important questions such as “Where
are sales growing,” “What is driving growth” and “What
are the characteristics of my customers using different
services?” By using Tableau visualizations, you gain the
ability to quickly answer questions; your data becomes
a competitive advantage instead of an underutilized
asset.
Slide 27Slide 27Slide 27 www.edureka.co/data-warehousing-and-bi
Tableau Software, Inc.
Company and Leadership
• The company was founded in Mountain View, California in January, 2003 by
Chris Stolte, Christian Chabot and Pat Hanrahan.
• Based on a breakthrough from Stanford University, Tableau makes visual
analytics and business intelligence software that delivers:
• 10-100X productivity improvements
• amazing multi-dimensional discoveries
• web analytics at 1/10th the cost of a “BI Platform”
The company is headquartered in Seattle, WA.
Customers
+ Google
+ Allstate
+ Cornell
+ Harvard
+ Apple
+ NSA
+ Microsoft
+ 1,000’s more
Key Partners
+ Oracle OEM
+ Microsoft Gold Certified
+ Teradata Partner
Slide 28Slide 28Slide 28 www.edureka.co/data-warehousing-and-bi
Customers: 4,000 Strong Companies
Advertising and Marketing
Avenue A | Razorfish
DoubleClick
Draft FCB
Olgilvy
Predicta Brazil
The Martin Agency
Banking and Finance
Bank of America
Barclays Global
Citigroup
Draft FCB Group
EverBank Direct
Fifth Third Bank
Greater Iowa Credit Union
Wells Fargo
Charities
British Red Cross
Christian Relief Services Charities
DC Children & Youth Inv. Trust Corp.
Goodwill Industries
United Way of Rock River Valley
World Vision
Communications
Bell Canada
Bell South
FiberTower
Lucent
Mitel Networks Corporation
Motorola
Sprint
T-Mobile
Telstra
Verizon Communications
Consulting and Legal
Baker & McKenzie
Booz Allen Hamilton
Clorox Company
Cornerstone Research
Deloitte & Touche LLP
Electronic Data Systems Corporation
Ernst & Young
McKinsey & Company
Mercer
Norbridge
Energy & Utilities
Atomic Energy of Canada
Duke Energy Corporation
Louisville Water Company
Omaha Public Power District
Saudi Aramco
TXU
Williams Midstream
WindLogics
Engineering and Construction
Bechtel Corporation
Beezer Homes
Kiewit Corporation
McGraw-Hill Construction
St. Onge Company
Financial Information
Dunn & Bradstreet
Equifax
Fannie Mae
HTM Corporation
Moodys Investors Service
Scottish Re
Standard and Poor's
Food and Beverage
Chicken of the Sea
Nestlé
Prairie Berry Winery
Sierra Nevada Brewing Company
Starbucks Coffee
The Coca-Cola Company
Turkey Hill Dairy
Healthcare
Barnes Jewish Hospital
Blue Cross Blue Shield of Alabama
Caremark
Good Shepherd Medical Center
Harvard Medical School
Johnson & Johnson
Kaleida Health
LSU Health Sciences
Roche Diagnostics
St. Jude Children's Research
University of Miami Medical Center
Wake Forest Health Sciences
Insurance
AAA Allied Group
Amica
Esurance
Marsh & McLennan
Mutual of Omaha
Nationwide Insurance
Progressive
The Regence Group
Investment and Brokerage
Bridgewater Associates
Charles Schwab
Dundee Securities
Merrill Lynch
National Financial Partners
New Enterprise Associates
RBC Dain Rauscher
Rosenblatt Securities
Stone Castle Partners
Manufacturing
Air Products
Alcoa
Boeing
Dow Chemical
Hitachi
Honda
Jabil Circuit
KLA Tencor
Lockheed Martin
Pratt & Whitney
Ricoh
Sony
Steelcase
Toyota
Media and Entertainment
CNET Networks
Discovery Communications
Dow Jones and Company
Epic Games
Microsoft Xbox
New York Times
O'Reilly Media
Sony
TiVo
Univision
Pharamceutical
Alza Pharmaceutical
Cephalon
Eli Lilly
Johnson & Johnson
McKesson
Merck
Novo Nordisk
Pfizer
Sanofi Aventis
Government and Public Sector
Australia Attorney General
DC Government
Federal Aviation Administration (FAA)
Government of Canada
National Science Foundation
NSA - National Security Agency
NYC Department of Education
Pacific Northwest National Lab (PNNL)
SOCOM - US Special Ops Command
US Air Force
US Army
US Bureau of Land Management
US Department of Agriculture (USDA)
US Department of Justice
US Department of the Navy
Veteran's Benefit Association (VBA)
Research & Development
Bayer CropScience
Boeing Phantomworks
General Electric Global Research
Lawrence Livermore Labs
MITRE
National Institute of Health
National Reconnaissance Office
National Visualization Analytics Center
Pacific Northwest National Labs
Quest Diagnostics
Retail
Amazon.com
Barnes & Noble
Borders
Caremark CVS
Lowe's
MAPCO
Pilot Travel LLC
Safeway
Walmart
Wet Seal
Service and Outsourcing
ADP
Computer Information Concepts
EDS
Hmetrix
Madrona Solutions Group
Oco
StrategicOne
Wolters Kluwer
Technology
Adobe
AOL
BEA Systems
CNET Networks
eBay
Electronic Arts
ESRI
Google
HP
IBM
Microsoft
MySQL
Novell
Pay Pal
VMWare
TechNexxus
Travel & Leisure
Alaska Airlines
Bourne Leisure
Celebrity Cruise Lines
Expedia
Royal Caribbean Cruise Lines
Sandiego.com
Universities and Colleges
Appalachian State University
Chemetka Community College
Cornell University
DePaul University
Duke University
Georgetown University
Johns Hopkins University
London School of Economics
Ohio State University
Pitzer College
Providence College
San Diego State University
University College- Dublin
University of North Carolina – Chapel Hill
Slide 29Slide 29Slide 29 www.edureka.co/data-warehousing-and-bi
Tableau Products
Tableau Desktop
Create
Tableau Server
Share - Web
Tableau Reader
Share - Local
+ business intelligence
solution scales to
organizations of all sizes
+ share visual analytics with
anyone with a web
browser
+ publish interactive
analytics or dashboards
+ secure information and
manage metadata
+ collaborate with others
+ share visualizations &
dashboards on the
desktop
+ filter, sort, and page
through the views
+ “Acrobat for Data”
+ free download
+ ad hoc analytics,
dashboards, reports, graphs
+ explore, visualize, and
analyze your data
+ create dashboards to
consolidate multiple views
+ deliver interactive data
experiences
Tableau Public
Share - Everyone
+ create and publish
interactive visualizations
and dashboards
+ embed in websites and
blogs
+ free download and free
hosting service
Slide 30Slide 30Slide 30 www.edureka.co/data-warehousing-and-bi
How Do People Work With Tableau
Slide 31 www.edureka.co/data-warehousing-and-bi
Tableau Public - Start Page
Questions
Slide 32 www.edureka.co/data-warehousing-and-bi
Mastering in data warehousing & BusinessIintelligence

More Related Content

What's hot

Data Vault Introduction
Data Vault IntroductionData Vault Introduction
Data Vault Introduction
Patrick Van Renterghem
 
The technology of the business data lake
The technology of the business data lakeThe technology of the business data lake
The technology of the business data lake
Capgemini
 
Improving the customer experience using big data customer-centric measurement...
Improving the customer experience using big data customer-centric measurement...Improving the customer experience using big data customer-centric measurement...
Improving the customer experience using big data customer-centric measurement...
Business Over Broadway
 
Microsoft Business Intelligence - Practical Approach & Overview
Microsoft Business Intelligence - Practical Approach & OverviewMicrosoft Business Intelligence - Practical Approach & Overview
Microsoft Business Intelligence - Practical Approach & Overview
Li Ken Chong
 
Agile BI via Data Vault and Modelstorming
Agile BI via Data Vault and ModelstormingAgile BI via Data Vault and Modelstorming
Agile BI via Data Vault and Modelstorming
Daniel Upton
 
Dw & etl concepts
Dw & etl conceptsDw & etl concepts
Dw & etl concepts
jeshocarme
 
Microsoft business intelligence
Microsoft business intelligenceMicrosoft business intelligence
Microsoft business intelligence
Jawad Mohmand
 
Bi Architecture And Conceptual Framework
Bi Architecture And Conceptual FrameworkBi Architecture And Conceptual Framework
Bi Architecture And Conceptual Framework
Slava Kokaev
 
Data warehouse
Data warehouseData warehouse
Data warehouse
Rishabh Dogra
 
SAP Data Services
SAP Data ServicesSAP Data Services
SAP Data Services
Geetika
 
Datawarehouse & bi introduction
Datawarehouse & bi introductionDatawarehouse & bi introduction
Datawarehouse & bi introduction
guest7b34c2
 
Traditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overviewTraditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overview
Nagaraj Yerram
 
Introduction to Data Warehousing
Introduction to Data WarehousingIntroduction to Data Warehousing
Introduction to Data Warehousing
Edureka!
 
Data Warehouse Design and Best Practices
Data Warehouse Design and Best PracticesData Warehouse Design and Best Practices
Data Warehouse Design and Best Practices
Ivo Andreev
 
Enterprise Services Solutions
Enterprise Services SolutionsEnterprise Services Solutions
Enterprise Services Solutions
Karya Technologies
 
Project+team+1 slides (2)
Project+team+1 slides (2)Project+team+1 slides (2)
Project+team+1 slides (2)
Vijay Pappu, Ph.D.
 
Rev_3 Components of a Data Warehouse
Rev_3 Components of a Data WarehouseRev_3 Components of a Data Warehouse
Rev_3 Components of a Data Warehouse
Ryan Andhavarapu
 
Bi presentation Designing and Implementing Business Intelligence Systems
Bi presentation   Designing and Implementing Business Intelligence SystemsBi presentation   Designing and Implementing Business Intelligence Systems
Bi presentation Designing and Implementing Business Intelligence Systems
Vispi Munshi
 
Data Provisioning & Optimization
Data Provisioning & OptimizationData Provisioning & Optimization
Data Provisioning & Optimization
Ambareesh Kulkarni
 
BP_SAP_MDM
BP_SAP_MDMBP_SAP_MDM

What's hot (20)

Data Vault Introduction
Data Vault IntroductionData Vault Introduction
Data Vault Introduction
 
The technology of the business data lake
The technology of the business data lakeThe technology of the business data lake
The technology of the business data lake
 
Improving the customer experience using big data customer-centric measurement...
Improving the customer experience using big data customer-centric measurement...Improving the customer experience using big data customer-centric measurement...
Improving the customer experience using big data customer-centric measurement...
 
Microsoft Business Intelligence - Practical Approach & Overview
Microsoft Business Intelligence - Practical Approach & OverviewMicrosoft Business Intelligence - Practical Approach & Overview
Microsoft Business Intelligence - Practical Approach & Overview
 
Agile BI via Data Vault and Modelstorming
Agile BI via Data Vault and ModelstormingAgile BI via Data Vault and Modelstorming
Agile BI via Data Vault and Modelstorming
 
Dw & etl concepts
Dw & etl conceptsDw & etl concepts
Dw & etl concepts
 
Microsoft business intelligence
Microsoft business intelligenceMicrosoft business intelligence
Microsoft business intelligence
 
Bi Architecture And Conceptual Framework
Bi Architecture And Conceptual FrameworkBi Architecture And Conceptual Framework
Bi Architecture And Conceptual Framework
 
Data warehouse
Data warehouseData warehouse
Data warehouse
 
SAP Data Services
SAP Data ServicesSAP Data Services
SAP Data Services
 
Datawarehouse & bi introduction
Datawarehouse & bi introductionDatawarehouse & bi introduction
Datawarehouse & bi introduction
 
Traditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overviewTraditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overview
 
Introduction to Data Warehousing
Introduction to Data WarehousingIntroduction to Data Warehousing
Introduction to Data Warehousing
 
Data Warehouse Design and Best Practices
Data Warehouse Design and Best PracticesData Warehouse Design and Best Practices
Data Warehouse Design and Best Practices
 
Enterprise Services Solutions
Enterprise Services SolutionsEnterprise Services Solutions
Enterprise Services Solutions
 
Project+team+1 slides (2)
Project+team+1 slides (2)Project+team+1 slides (2)
Project+team+1 slides (2)
 
Rev_3 Components of a Data Warehouse
Rev_3 Components of a Data WarehouseRev_3 Components of a Data Warehouse
Rev_3 Components of a Data Warehouse
 
Bi presentation Designing and Implementing Business Intelligence Systems
Bi presentation   Designing and Implementing Business Intelligence SystemsBi presentation   Designing and Implementing Business Intelligence Systems
Bi presentation Designing and Implementing Business Intelligence Systems
 
Data Provisioning & Optimization
Data Provisioning & OptimizationData Provisioning & Optimization
Data Provisioning & Optimization
 
BP_SAP_MDM
BP_SAP_MDMBP_SAP_MDM
BP_SAP_MDM
 

Viewers also liked

Is Data Scientist still the sexiest job of 21st century? Find Out!
Is Data Scientist still the sexiest job of 21st century? Find Out!Is Data Scientist still the sexiest job of 21st century? Find Out!
Is Data Scientist still the sexiest job of 21st century? Find Out!
Edureka!
 
Big Data Processing with Spark and Scala
Big Data Processing with Spark and Scala Big Data Processing with Spark and Scala
Big Data Processing with Spark and Scala
Edureka!
 
R and Visualization: A match made in Heaven
R and Visualization: A match made in HeavenR and Visualization: A match made in Heaven
R and Visualization: A match made in Heaven
Edureka!
 
Power of Python with Big Data
Power of Python with Big DataPower of Python with Big Data
Power of Python with Big Data
Edureka!
 
Big Data Analytics for Non-Programmers
Big Data Analytics for Non-ProgrammersBig Data Analytics for Non-Programmers
Big Data Analytics for Non-Programmers
Edureka!
 
Spark for big data analytics
Spark for big data analyticsSpark for big data analytics
Spark for big data analytics
Edureka!
 
Top 5 algorithms used in Data Science
Top 5 algorithms used in Data ScienceTop 5 algorithms used in Data Science
Top 5 algorithms used in Data Science
Edureka!
 
Clare Corthell: Learning Data Science Online
Clare Corthell: Learning Data Science OnlineClare Corthell: Learning Data Science Online
Clare Corthell: Learning Data Science Online
sfdatascience
 
Health care and big data with hadoop – Beacuse prevention is better than cure
Health care and big data with hadoop – Beacuse prevention is better than cureHealth care and big data with hadoop – Beacuse prevention is better than cure
Health care and big data with hadoop – Beacuse prevention is better than cure
Edureka!
 
Python for Big Data Analytics
Python for Big Data AnalyticsPython for Big Data Analytics
Python for Big Data Analytics
Edureka!
 
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
Edureka!
 
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Edureka!
 

Viewers also liked (12)

Is Data Scientist still the sexiest job of 21st century? Find Out!
Is Data Scientist still the sexiest job of 21st century? Find Out!Is Data Scientist still the sexiest job of 21st century? Find Out!
Is Data Scientist still the sexiest job of 21st century? Find Out!
 
Big Data Processing with Spark and Scala
Big Data Processing with Spark and Scala Big Data Processing with Spark and Scala
Big Data Processing with Spark and Scala
 
R and Visualization: A match made in Heaven
R and Visualization: A match made in HeavenR and Visualization: A match made in Heaven
R and Visualization: A match made in Heaven
 
Power of Python with Big Data
Power of Python with Big DataPower of Python with Big Data
Power of Python with Big Data
 
Big Data Analytics for Non-Programmers
Big Data Analytics for Non-ProgrammersBig Data Analytics for Non-Programmers
Big Data Analytics for Non-Programmers
 
Spark for big data analytics
Spark for big data analyticsSpark for big data analytics
Spark for big data analytics
 
Top 5 algorithms used in Data Science
Top 5 algorithms used in Data ScienceTop 5 algorithms used in Data Science
Top 5 algorithms used in Data Science
 
Clare Corthell: Learning Data Science Online
Clare Corthell: Learning Data Science OnlineClare Corthell: Learning Data Science Online
Clare Corthell: Learning Data Science Online
 
Health care and big data with hadoop – Beacuse prevention is better than cure
Health care and big data with hadoop – Beacuse prevention is better than cureHealth care and big data with hadoop – Beacuse prevention is better than cure
Health care and big data with hadoop – Beacuse prevention is better than cure
 
Python for Big Data Analytics
Python for Big Data AnalyticsPython for Big Data Analytics
Python for Big Data Analytics
 
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...
 
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
 

Similar to Mastering in data warehousing & BusinessIintelligence

What is a Data Warehouse and How Do I Test It?
What is a Data Warehouse and How Do I Test It?What is a Data Warehouse and How Do I Test It?
What is a Data Warehouse and How Do I Test It?
RTTS
 
How to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
How to Optimize Sales Analytics Using 10x the Data at 1/10th the CostHow to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
How to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
AtScale
 
Big Data Discovery
Big Data DiscoveryBig Data Discovery
Big Data Discovery
Harald Erb
 
Data warehousing
Data warehousingData warehousing
Data warehousing
Juhi Mahajan
 
MT101 Dell OCIO: Delivering data and analytics in real time
MT101 Dell OCIO:  Delivering data and analytics in real timeMT101 Dell OCIO:  Delivering data and analytics in real time
MT101 Dell OCIO: Delivering data and analytics in real time
Dell EMC World
 
Abdul ETL Resume
Abdul ETL ResumeAbdul ETL Resume
Abdul ETL Resume
Abdul mohammed
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
DATAVERSITY
 
Resume
ResumeResume
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BI
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BIAugmentation, Collaboration, Governance: Defining the Future of Self-Service BI
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BI
Denodo
 
Accelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and VisualizationAccelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and Visualization
Denodo
 
Big Data's Impact on the Enterprise
Big Data's Impact on the EnterpriseBig Data's Impact on the Enterprise
Big Data's Impact on the Enterprise
Caserta
 
Building a strong Data Management capability with TOGAF and ArchiMate
Building a strong Data Management capability with TOGAF and ArchiMateBuilding a strong Data Management capability with TOGAF and ArchiMate
Building a strong Data Management capability with TOGAF and ArchiMate
Bas van Gils
 
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
Enterprise Management Associates
 
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONSTRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
Taction Software LLC
 
Building the Artificially Intelligent Enterprise
Building the Artificially Intelligent EnterpriseBuilding the Artificially Intelligent Enterprise
Building the Artificially Intelligent Enterprise
Databricks
 
DataWarehousingandAbInitioConcepts.ppt
DataWarehousingandAbInitioConcepts.pptDataWarehousingandAbInitioConcepts.ppt
DataWarehousingandAbInitioConcepts.ppt
PurnenduMaity2
 
Analytic Excellence - Saying Goodbye to Old Constraints
Analytic Excellence - Saying Goodbye to Old ConstraintsAnalytic Excellence - Saying Goodbye to Old Constraints
Analytic Excellence - Saying Goodbye to Old Constraints
Inside Analysis
 
Msbi by quontra us
Msbi by quontra usMsbi by quontra us
Msbi by quontra us
QUONTRASOLUTIONS
 
What is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
What is OLAP -Data Warehouse Concepts - IT Online Training @ NewyorksysWhat is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
What is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
NEWYORKSYS-IT SOLUTIONS
 
Kiran Infromatica developer
Kiran Infromatica developerKiran Infromatica developer
Kiran Infromatica developer
Kiran Annamaneni
 

Similar to Mastering in data warehousing & BusinessIintelligence (20)

What is a Data Warehouse and How Do I Test It?
What is a Data Warehouse and How Do I Test It?What is a Data Warehouse and How Do I Test It?
What is a Data Warehouse and How Do I Test It?
 
How to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
How to Optimize Sales Analytics Using 10x the Data at 1/10th the CostHow to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
How to Optimize Sales Analytics Using 10x the Data at 1/10th the Cost
 
Big Data Discovery
Big Data DiscoveryBig Data Discovery
Big Data Discovery
 
Data warehousing
Data warehousingData warehousing
Data warehousing
 
MT101 Dell OCIO: Delivering data and analytics in real time
MT101 Dell OCIO:  Delivering data and analytics in real timeMT101 Dell OCIO:  Delivering data and analytics in real time
MT101 Dell OCIO: Delivering data and analytics in real time
 
Abdul ETL Resume
Abdul ETL ResumeAbdul ETL Resume
Abdul ETL Resume
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
 
Resume
ResumeResume
Resume
 
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BI
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BIAugmentation, Collaboration, Governance: Defining the Future of Self-Service BI
Augmentation, Collaboration, Governance: Defining the Future of Self-Service BI
 
Accelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and VisualizationAccelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and Visualization
 
Big Data's Impact on the Enterprise
Big Data's Impact on the EnterpriseBig Data's Impact on the Enterprise
Big Data's Impact on the Enterprise
 
Building a strong Data Management capability with TOGAF and ArchiMate
Building a strong Data Management capability with TOGAF and ArchiMateBuilding a strong Data Management capability with TOGAF and ArchiMate
Building a strong Data Management capability with TOGAF and ArchiMate
 
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
How to Merge the Data Lake and the Data Warehouse: The Power of a Unified Ana...
 
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONSTRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONS
 
Building the Artificially Intelligent Enterprise
Building the Artificially Intelligent EnterpriseBuilding the Artificially Intelligent Enterprise
Building the Artificially Intelligent Enterprise
 
DataWarehousingandAbInitioConcepts.ppt
DataWarehousingandAbInitioConcepts.pptDataWarehousingandAbInitioConcepts.ppt
DataWarehousingandAbInitioConcepts.ppt
 
Analytic Excellence - Saying Goodbye to Old Constraints
Analytic Excellence - Saying Goodbye to Old ConstraintsAnalytic Excellence - Saying Goodbye to Old Constraints
Analytic Excellence - Saying Goodbye to Old Constraints
 
Msbi by quontra us
Msbi by quontra usMsbi by quontra us
Msbi by quontra us
 
What is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
What is OLAP -Data Warehouse Concepts - IT Online Training @ NewyorksysWhat is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
What is OLAP -Data Warehouse Concepts - IT Online Training @ Newyorksys
 
Kiran Infromatica developer
Kiran Infromatica developerKiran Infromatica developer
Kiran Infromatica developer
 

More from Edureka!

What to learn during the 21 days Lockdown | Edureka
What to learn during the 21 days Lockdown | EdurekaWhat to learn during the 21 days Lockdown | Edureka
What to learn during the 21 days Lockdown | Edureka
Edureka!
 
Top 10 Dying Programming Languages in 2020 | Edureka
Top 10 Dying Programming Languages in 2020 | EdurekaTop 10 Dying Programming Languages in 2020 | Edureka
Top 10 Dying Programming Languages in 2020 | Edureka
Edureka!
 
Top 5 Trending Business Intelligence Tools | Edureka
Top 5 Trending Business Intelligence Tools | EdurekaTop 5 Trending Business Intelligence Tools | Edureka
Top 5 Trending Business Intelligence Tools | Edureka
Edureka!
 
Tableau Tutorial for Data Science | Edureka
Tableau Tutorial for Data Science | EdurekaTableau Tutorial for Data Science | Edureka
Tableau Tutorial for Data Science | Edureka
Edureka!
 
Python Programming Tutorial | Edureka
Python Programming Tutorial | EdurekaPython Programming Tutorial | Edureka
Python Programming Tutorial | Edureka
Edureka!
 
Top 5 PMP Certifications | Edureka
Top 5 PMP Certifications | EdurekaTop 5 PMP Certifications | Edureka
Top 5 PMP Certifications | Edureka
Edureka!
 
Top Maven Interview Questions in 2020 | Edureka
Top Maven Interview Questions in 2020 | EdurekaTop Maven Interview Questions in 2020 | Edureka
Top Maven Interview Questions in 2020 | Edureka
Edureka!
 
Linux Mint Tutorial | Edureka
Linux Mint Tutorial | EdurekaLinux Mint Tutorial | Edureka
Linux Mint Tutorial | Edureka
Edureka!
 
How to Deploy Java Web App in AWS| Edureka
How to Deploy Java Web App in AWS| EdurekaHow to Deploy Java Web App in AWS| Edureka
How to Deploy Java Web App in AWS| Edureka
Edureka!
 
Importance of Digital Marketing | Edureka
Importance of Digital Marketing | EdurekaImportance of Digital Marketing | Edureka
Importance of Digital Marketing | Edureka
Edureka!
 
RPA in 2020 | Edureka
RPA in 2020 | EdurekaRPA in 2020 | Edureka
RPA in 2020 | Edureka
Edureka!
 
Email Notifications in Jenkins | Edureka
Email Notifications in Jenkins | EdurekaEmail Notifications in Jenkins | Edureka
Email Notifications in Jenkins | Edureka
Edureka!
 
EA Algorithm in Machine Learning | Edureka
EA Algorithm in Machine Learning | EdurekaEA Algorithm in Machine Learning | Edureka
EA Algorithm in Machine Learning | Edureka
Edureka!
 
Cognitive AI Tutorial | Edureka
Cognitive AI Tutorial | EdurekaCognitive AI Tutorial | Edureka
Cognitive AI Tutorial | Edureka
Edureka!
 
AWS Cloud Practitioner Tutorial | Edureka
AWS Cloud Practitioner Tutorial | EdurekaAWS Cloud Practitioner Tutorial | Edureka
AWS Cloud Practitioner Tutorial | Edureka
Edureka!
 
Blue Prism Top Interview Questions | Edureka
Blue Prism Top Interview Questions | EdurekaBlue Prism Top Interview Questions | Edureka
Blue Prism Top Interview Questions | Edureka
Edureka!
 
Big Data on AWS Tutorial | Edureka
Big Data on AWS Tutorial | Edureka Big Data on AWS Tutorial | Edureka
Big Data on AWS Tutorial | Edureka
Edureka!
 
A star algorithm | A* Algorithm in Artificial Intelligence | Edureka
A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaA star algorithm | A* Algorithm in Artificial Intelligence | Edureka
A star algorithm | A* Algorithm in Artificial Intelligence | Edureka
Edureka!
 
Kubernetes Installation on Ubuntu | Edureka
Kubernetes Installation on Ubuntu | EdurekaKubernetes Installation on Ubuntu | Edureka
Kubernetes Installation on Ubuntu | Edureka
Edureka!
 
Introduction to DevOps | Edureka
Introduction to DevOps | EdurekaIntroduction to DevOps | Edureka
Introduction to DevOps | Edureka
Edureka!
 

More from Edureka! (20)

What to learn during the 21 days Lockdown | Edureka
What to learn during the 21 days Lockdown | EdurekaWhat to learn during the 21 days Lockdown | Edureka
What to learn during the 21 days Lockdown | Edureka
 
Top 10 Dying Programming Languages in 2020 | Edureka
Top 10 Dying Programming Languages in 2020 | EdurekaTop 10 Dying Programming Languages in 2020 | Edureka
Top 10 Dying Programming Languages in 2020 | Edureka
 
Top 5 Trending Business Intelligence Tools | Edureka
Top 5 Trending Business Intelligence Tools | EdurekaTop 5 Trending Business Intelligence Tools | Edureka
Top 5 Trending Business Intelligence Tools | Edureka
 
Tableau Tutorial for Data Science | Edureka
Tableau Tutorial for Data Science | EdurekaTableau Tutorial for Data Science | Edureka
Tableau Tutorial for Data Science | Edureka
 
Python Programming Tutorial | Edureka
Python Programming Tutorial | EdurekaPython Programming Tutorial | Edureka
Python Programming Tutorial | Edureka
 
Top 5 PMP Certifications | Edureka
Top 5 PMP Certifications | EdurekaTop 5 PMP Certifications | Edureka
Top 5 PMP Certifications | Edureka
 
Top Maven Interview Questions in 2020 | Edureka
Top Maven Interview Questions in 2020 | EdurekaTop Maven Interview Questions in 2020 | Edureka
Top Maven Interview Questions in 2020 | Edureka
 
Linux Mint Tutorial | Edureka
Linux Mint Tutorial | EdurekaLinux Mint Tutorial | Edureka
Linux Mint Tutorial | Edureka
 
How to Deploy Java Web App in AWS| Edureka
How to Deploy Java Web App in AWS| EdurekaHow to Deploy Java Web App in AWS| Edureka
How to Deploy Java Web App in AWS| Edureka
 
Importance of Digital Marketing | Edureka
Importance of Digital Marketing | EdurekaImportance of Digital Marketing | Edureka
Importance of Digital Marketing | Edureka
 
RPA in 2020 | Edureka
RPA in 2020 | EdurekaRPA in 2020 | Edureka
RPA in 2020 | Edureka
 
Email Notifications in Jenkins | Edureka
Email Notifications in Jenkins | EdurekaEmail Notifications in Jenkins | Edureka
Email Notifications in Jenkins | Edureka
 
EA Algorithm in Machine Learning | Edureka
EA Algorithm in Machine Learning | EdurekaEA Algorithm in Machine Learning | Edureka
EA Algorithm in Machine Learning | Edureka
 
Cognitive AI Tutorial | Edureka
Cognitive AI Tutorial | EdurekaCognitive AI Tutorial | Edureka
Cognitive AI Tutorial | Edureka
 
AWS Cloud Practitioner Tutorial | Edureka
AWS Cloud Practitioner Tutorial | EdurekaAWS Cloud Practitioner Tutorial | Edureka
AWS Cloud Practitioner Tutorial | Edureka
 
Blue Prism Top Interview Questions | Edureka
Blue Prism Top Interview Questions | EdurekaBlue Prism Top Interview Questions | Edureka
Blue Prism Top Interview Questions | Edureka
 
Big Data on AWS Tutorial | Edureka
Big Data on AWS Tutorial | Edureka Big Data on AWS Tutorial | Edureka
Big Data on AWS Tutorial | Edureka
 
A star algorithm | A* Algorithm in Artificial Intelligence | Edureka
A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaA star algorithm | A* Algorithm in Artificial Intelligence | Edureka
A star algorithm | A* Algorithm in Artificial Intelligence | Edureka
 
Kubernetes Installation on Ubuntu | Edureka
Kubernetes Installation on Ubuntu | EdurekaKubernetes Installation on Ubuntu | Edureka
Kubernetes Installation on Ubuntu | Edureka
 
Introduction to DevOps | Edureka
Introduction to DevOps | EdurekaIntroduction to DevOps | Edureka
Introduction to DevOps | Edureka
 

Recently uploaded

GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Zilliz
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
KAMESHS29
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
SOFTTECHHUB
 
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceAI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
IndexBug
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Safe Software
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
GenAI Pilot Implementation in the organizations
GenAI Pilot Implementation in the organizationsGenAI Pilot Implementation in the organizations
GenAI Pilot Implementation in the organizations
kumardaparthi1024
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
Adtran
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 

Recently uploaded (20)

GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
 
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceAI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
GenAI Pilot Implementation in the organizations
GenAI Pilot Implementation in the organizationsGenAI Pilot Implementation in the organizations
GenAI Pilot Implementation in the organizations
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 

Mastering in data warehousing & BusinessIintelligence

  • 2. Slide 2 www.edureka.co/data-warehousing-and-bi At the end of this module, you will be able to Know : Objective  What is Data Warehousing & Business Intelligence ?  What is Data Warehousing Architecture ?  What is Data Modelling / Introduction to ER Win r9 Tool ?  What is ETL / An Open Source ETL Tool – Talend 5.x ?  What is Business Intelligence / An Open Source Tableau Public 9.x ?
  • 3. Slide 3Slide 3Slide 3 www.edureka.co/data-warehousing-and-bi What is Data Warehouse A data warehouse refers to a database that is maintained separately from an organization’s operational database “A data warehouse is a subject-oriented, integrated, time- variant, and nonvolatile collection of data in support of management’s decision-making process.” Loosely Speaking Officially Speaking W.H. Inmon
  • 4. Slide 4Slide 4Slide 4 www.edureka.co/data-warehousing-and-bi Subject Oriented Data Warehouse Properties Non Volatile Integrated Time Variant Data Warehousing
  • 5. Slide 5Slide 5Slide 5 www.edureka.co/data-warehousing-and-bi Subject-Oriented Data is categorized and stored by business subject rather than by application Equity Plans Shares Customer financial information Savings Insurance Loans OLTP Applications Data Warehouse Subject
  • 6. Slide 6Slide 6Slide 6 www.edureka.co/data-warehousing-and-bi Integrated OLTP Applications Savings Current accounts Loans Data Warehouse Data on a given subject is defined and stored once. Customer
  • 7. Slide 7Slide 7Slide 7 www.edureka.co/data-warehousing-and-bi Time-Variant Data is stored as a series of snapshots, each representing a period of time… TIME DATA Jan-97 January Feb-97 February Mar-97 March Jan-97 January
  • 8. Slide 8Slide 8Slide 8 www.edureka.co/data-warehousing-and-bi Non-Volatile Typically data in the data warehouse is not updated or deleted. Insert Update Delete Read Read Operational Warehouse Load
  • 9. Slide 9Slide 9Slide 9 www.edureka.co/data-warehousing-and-bi Changing Data Warehouse Database First time load Refresh Refresh Operational Database
  • 10. Slide 10Slide 10Slide 10 www.edureka.co/data-warehousing-and-bi What is Data Warehouse “Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.” Officially Speaking Ralph Kimball
  • 11. Slide 11Slide 11Slide 11 www.edureka.co/data-warehousing-and-bi InmonVsRalphKimball Characteristics Inmon Kimball Business Decision Support Requirements Strategic Tactical Data Integration Requirement Enterprise Wise Integrator Individual Business Requirement Data Structure Requirement Data that meet multiple and varied information needs and non-metric data KPI, Business Performance Measure & Scorecards Requirements Persistency of Data in Source System Source Systems have high rate of change Source Systems are quite stable Skill Sets Bigger Team of Specialists Small Team of Generalists Time Constraint Longer Time Required Urgent delivery as this is subjective Cost to Build High Start-up Costs Low Start-Up Costs
  • 12. Slide 12Slide 12Slide 12 www.edureka.co/data-warehousing-and-bi Data Ware Housing Products Entity Relationship / Schema Modeling Data Integration / ETL
  • 13. Slide 13Slide 13Slide 13 www.edureka.co/data-warehousing-and-bi What is Business Intelligence? Business intelligence (BI) is the set of techniques and tools for the transformation of raw / production and operational data into meaningful and useful information for business analysis purposes for various level. Business intelligence (BI) talks about how traditional data which transform into the BI which have multiple initiatives to measure, manage, and improve on the performance of individuals, processes, teams, and business units for the specific business area. During the operation of business, the following questions must be asked. The functions of monitoring, analyzing, and planning delve into these questions as follows : • What has happened? • What is happening? • Why? • What will happen? • What do we want to have happen?
  • 14. Slide 14Slide 14Slide 14 www.edureka.co/data-warehousing-and-bi What is Business Intelligence Categories? Strategic Business Intelligence: Management collaborates and agrees on a strategy and a method in which they would like to see information presented, for example, in maps, scorecards, reports, or dashboards. Now that you have your strategy defined, it is imperative that you do something with the data that you have collected Analytical Business Intelligence: Once Strategic BI sets the foundation in the form of key performance metrics, then Analytical BI is employed to identify the source of an issue once it has been uncovered. Tools like analytic dashboards, OLAP, predictive analytics, and ad hoc queries are utilized to determine the location or the cause of a major problem.
  • 16. Slide 16Slide 16Slide 16 www.edureka.co/data-warehousing-and-bi - CA ERwin Introduction • ERwin is a popular data modeling tool used by a number of major companies throughout the world. The product is currently owned, developed, and marketed by Computer Associates, a leading software company. • The product supports a variety of aspects of database design, including data modeling, forward engineering (the creation of a database schema and physical database on the basis of a data model), and reverse engineering (the creation of a data model on the basis of an existing database) for a wide variety of relational DBMS, including Microsoft Access, Oracle, DB2, Sybase, and others.
  • 17. Slide 17Slide 17Slide 17 www.edureka.co/data-warehousing-and-bi Physical ER Diagram
  • 18. Slide 18Slide 18Slide 18 www.edureka.co/data-warehousing-and-bi Open Source VS Commercial ETL Tools Open Source ETL Commercial ETL License Details Licensing Model Open-Core Model. No charges for extra CPU cycles Core Model. Extra usage charges can be applied for over-the-limit CPU cycles Licensing Channel via GNU public license/Apache license Vendor specific Cost Differentiation License Costs 30-60% < 1X times Commercial license (Mostly) 1X times Support and Maintenance Costs Close to Commercial vendor costs (Mostly) Close to Open-Source Advanced Features Offered through "Commercial" Open- Source Add-ons Type of Support and Maintenance Tiered pricing model. E.g. Community(Free, Forums), Silver, Gold and Platinum Editions Not offered in tiers (Mostly). Add-on to licensing costs
  • 19. Slide 19Slide 19Slide 19 www.edureka.co/data-warehousing-and-bi Talend Open DI Studio 5.x - Overview • Talend Open Studio for Data Integration operates as a code generator, producing data-transformation scripts and underlying programs in Java. Its GUI gives access to a metadata repository and to a graphical designer. The metadata repository contains the definitions and configuration for each job - but not the actual data being transformed or moved. All of the components of Talend Open Studio for Data Integration use the information in the metadata repository. • The product is based on Eclipse. • Talend Open DI Studio typically use for: • synchronization or replication of databases • right-time or batch exchanges of data • ETL (Extract/Transform/Load) for analytics • data migration • complex data transformation and loading • data quality exercises • big data • Talend Open Studio for Data Integration primarily differs from Talend Enterprise Data Integration in that the Enterprise version has a Subversion plug-in built in, as well as support for joblets. Using Talend Enterprise Data Integration, ETL and ELT jobs can have a dynamic schema.
  • 20. Slide 20Slide 20Slide 20 www.edureka.co/data-warehousing-and-bi Talend - History
  • 21. Slide 21Slide 21Slide 21 www.edureka.co/data-warehousing-and-bi Talend - Partners
  • 22. Slide 22Slide 22Slide 22 www.edureka.co/data-warehousing-and-bi Talend - Customers
  • 23. Slide 23Slide 23Slide 23 www.edureka.co/data-warehousing-and-bi Talend - Market Position
  • 24. Slide 24Slide 24Slide 24 www.edureka.co/data-warehousing-and-bi Talend - Product Offering
  • 25. Slide 25Slide 25Slide 25 www.edureka.co/data-warehousing-and-bi Talend DI Studio - Welcome Page
  • 26. Slide 26Slide 26Slide 26 www.edureka.co/data-warehousing-and-bi Data visualization With Tableau • Data visualization tools allow anyone to organize and present information intuitively. This is becoming more vital as data proliferates in every field from bar codes in retail stores to player behavior in online games. • All of this data is meaningless without a way to organize and present important findings within it. People comprehend data better through pictures than by reading numbers in rows and columns. • So by visualizing data, you are able to more effectively ask and answer important questions such as “Where are sales growing,” “What is driving growth” and “What are the characteristics of my customers using different services?” By using Tableau visualizations, you gain the ability to quickly answer questions; your data becomes a competitive advantage instead of an underutilized asset.
  • 27. Slide 27Slide 27Slide 27 www.edureka.co/data-warehousing-and-bi Tableau Software, Inc. Company and Leadership • The company was founded in Mountain View, California in January, 2003 by Chris Stolte, Christian Chabot and Pat Hanrahan. • Based on a breakthrough from Stanford University, Tableau makes visual analytics and business intelligence software that delivers: • 10-100X productivity improvements • amazing multi-dimensional discoveries • web analytics at 1/10th the cost of a “BI Platform” The company is headquartered in Seattle, WA. Customers + Google + Allstate + Cornell + Harvard + Apple + NSA + Microsoft + 1,000’s more Key Partners + Oracle OEM + Microsoft Gold Certified + Teradata Partner
  • 28. Slide 28Slide 28Slide 28 www.edureka.co/data-warehousing-and-bi Customers: 4,000 Strong Companies Advertising and Marketing Avenue A | Razorfish DoubleClick Draft FCB Olgilvy Predicta Brazil The Martin Agency Banking and Finance Bank of America Barclays Global Citigroup Draft FCB Group EverBank Direct Fifth Third Bank Greater Iowa Credit Union Wells Fargo Charities British Red Cross Christian Relief Services Charities DC Children & Youth Inv. Trust Corp. Goodwill Industries United Way of Rock River Valley World Vision Communications Bell Canada Bell South FiberTower Lucent Mitel Networks Corporation Motorola Sprint T-Mobile Telstra Verizon Communications Consulting and Legal Baker & McKenzie Booz Allen Hamilton Clorox Company Cornerstone Research Deloitte & Touche LLP Electronic Data Systems Corporation Ernst & Young McKinsey & Company Mercer Norbridge Energy & Utilities Atomic Energy of Canada Duke Energy Corporation Louisville Water Company Omaha Public Power District Saudi Aramco TXU Williams Midstream WindLogics Engineering and Construction Bechtel Corporation Beezer Homes Kiewit Corporation McGraw-Hill Construction St. Onge Company Financial Information Dunn & Bradstreet Equifax Fannie Mae HTM Corporation Moodys Investors Service Scottish Re Standard and Poor's Food and Beverage Chicken of the Sea Nestlé Prairie Berry Winery Sierra Nevada Brewing Company Starbucks Coffee The Coca-Cola Company Turkey Hill Dairy Healthcare Barnes Jewish Hospital Blue Cross Blue Shield of Alabama Caremark Good Shepherd Medical Center Harvard Medical School Johnson & Johnson Kaleida Health LSU Health Sciences Roche Diagnostics St. Jude Children's Research University of Miami Medical Center Wake Forest Health Sciences Insurance AAA Allied Group Amica Esurance Marsh & McLennan Mutual of Omaha Nationwide Insurance Progressive The Regence Group Investment and Brokerage Bridgewater Associates Charles Schwab Dundee Securities Merrill Lynch National Financial Partners New Enterprise Associates RBC Dain Rauscher Rosenblatt Securities Stone Castle Partners Manufacturing Air Products Alcoa Boeing Dow Chemical Hitachi Honda Jabil Circuit KLA Tencor Lockheed Martin Pratt & Whitney Ricoh Sony Steelcase Toyota Media and Entertainment CNET Networks Discovery Communications Dow Jones and Company Epic Games Microsoft Xbox New York Times O'Reilly Media Sony TiVo Univision Pharamceutical Alza Pharmaceutical Cephalon Eli Lilly Johnson & Johnson McKesson Merck Novo Nordisk Pfizer Sanofi Aventis Government and Public Sector Australia Attorney General DC Government Federal Aviation Administration (FAA) Government of Canada National Science Foundation NSA - National Security Agency NYC Department of Education Pacific Northwest National Lab (PNNL) SOCOM - US Special Ops Command US Air Force US Army US Bureau of Land Management US Department of Agriculture (USDA) US Department of Justice US Department of the Navy Veteran's Benefit Association (VBA) Research & Development Bayer CropScience Boeing Phantomworks General Electric Global Research Lawrence Livermore Labs MITRE National Institute of Health National Reconnaissance Office National Visualization Analytics Center Pacific Northwest National Labs Quest Diagnostics Retail Amazon.com Barnes & Noble Borders Caremark CVS Lowe's MAPCO Pilot Travel LLC Safeway Walmart Wet Seal Service and Outsourcing ADP Computer Information Concepts EDS Hmetrix Madrona Solutions Group Oco StrategicOne Wolters Kluwer Technology Adobe AOL BEA Systems CNET Networks eBay Electronic Arts ESRI Google HP IBM Microsoft MySQL Novell Pay Pal VMWare TechNexxus Travel & Leisure Alaska Airlines Bourne Leisure Celebrity Cruise Lines Expedia Royal Caribbean Cruise Lines Sandiego.com Universities and Colleges Appalachian State University Chemetka Community College Cornell University DePaul University Duke University Georgetown University Johns Hopkins University London School of Economics Ohio State University Pitzer College Providence College San Diego State University University College- Dublin University of North Carolina – Chapel Hill
  • 29. Slide 29Slide 29Slide 29 www.edureka.co/data-warehousing-and-bi Tableau Products Tableau Desktop Create Tableau Server Share - Web Tableau Reader Share - Local + business intelligence solution scales to organizations of all sizes + share visual analytics with anyone with a web browser + publish interactive analytics or dashboards + secure information and manage metadata + collaborate with others + share visualizations & dashboards on the desktop + filter, sort, and page through the views + “Acrobat for Data” + free download + ad hoc analytics, dashboards, reports, graphs + explore, visualize, and analyze your data + create dashboards to consolidate multiple views + deliver interactive data experiences Tableau Public Share - Everyone + create and publish interactive visualizations and dashboards + embed in websites and blogs + free download and free hosting service
  • 30. Slide 30Slide 30Slide 30 www.edureka.co/data-warehousing-and-bi How Do People Work With Tableau