SlideShare a Scribd company logo
www.sadasengine.com
Data Warehouse
WHAT IS DWH?
THE PROBLEM
“A data warehouse is a copy of transaction data specifically structured for query and analysis.”
“A subject oriented, integrated, time variant, and non-volatile collection of summary and
detailed historical data used to support the strategic decision-making processes for the
corporation.”
“A data warehouse is the central storage point of all of the relevant information that is needed
for BI reports.[…] a major part of the effort of creating a data warehouse is obtaining the big
picture of what data exist, how is defined, and what the end result should look like.”
“A data warehouse is a storage architecture designed to hold data extracted from transaction
systems, operational data stores and external sources. The warehouse then combines that data
in an aggregate, summary form suitable for enterprise-wide data analysis and reporting for
predefined business needs.”
Ralph Kimball
William H. Inmon
Chris Bradley
Gartner Glossary
Data Sources Data Acquisition Data Storage Data Analysis Reporting & Visualization
Feeds (Rewrite, Append, Update)
Streams Apps
Source Systems
OLTP, EDWFiles
SQL
ODBC
JDBC
SCI
Multidimensional
Analysis
Data
Mining
Analytics
Reporting
ETL,
Replication,
Data Quality
SQL, ODBC,
JDBC, SCI
• Multidimensional
Analysis
• Analytics Reporting
• Data Mining
ETL,
Replication,
Data Quality Feeds (Rewrite, Append, Update)
A Data Warehouse essentially stores data, but there are also a lot of other activities it has to carry out: extract,
transform and load data as well as retrieve and analyze it. This is necessary for business intelligence purposes
in particular: retrieving and managing data effectively is crucial to gain useful information and allow for the best
decision making.
ETL time may be a pain point because the size of data is often huge. In fact, the quality of analysis depends on
the volume of the information loaded in the data warehouse. On the other hand, query time is critical as well,
especially for ad hoc analyses.
Data Warehouse
We provide software and services for data analysis in various and heterogeneous sectors, together with a range of cutting-edge Business Intelligence
solutions. SADAS operates in many industries: banking, leasing, government, insurance, media & telco and retail.
To know more about our products, visit our website www.sadasengine.com, or email us at sadasengine@sadasengine.com
MILANO Headquarters
Via Boschetti, 1 • 20121, Milano
Tel: +39 02 29017449
ROMA Sales Management
Via Principessa Clotilde, 7 • 00196, Roma
Tel: +39 06 83089713
BATH Consulting & Training Services
1 Priory Close • Bath, BA2 5AL, UK
Tel: +44 1225637004
SAN FRANCISCO USA International Office
20 California St. 7th floor • San Francisco, CA, 94111, USA
Tel: +1 415 429 3969
NAPOLI Registered Offices, R&D, Customer Service
Via Napoli, 159 • 80013, Casalnuovo di Napoli (NA)
Tel: +39 081 8427112 / fax: +39 081 8427171
Our solution benefits from the characteristics of Sadas Engine, our flagship
product: a columnar DBMS specifically designed to achieve outstanding
performances in Data Warehouse environments. Sadas Engine is a revolutionary
DBMS that meets companies’ needs in their daily activities of sourcing,
analyzing and managing data. It is easy to integrate and very efficient in all ETL
activities. Moreover, its front-end for dashboard & reporting works
out-of-the-box.
Columnar database
efficient, fast, reliable and not expensive.
Specific technology
innovative indexes and structures, “Intelligent Upload” phase and “Learn by Usage”approach, i.e.
capability to self adapt to new usage conditions.
One stop shop
all you need for data warehouse implementation, load and usage.
Off-the-shelf hardware
no need for expensive appliances or third party licenses.
SADAS SOLUTION FOR DATA WAREHOUSING
FEATURES & FUNCTIONS
High Performances:
the fastest and most efficient solution to ensure outstanding results on loading and analysis activities.
Low TCO:
running on low cost hardware & smart licensing allow Sadas to cut your TCO.
Quick implementation:
quick set-up process to save time, allowing for better design & analysis.
Reduced maintenance cost:
no DBA interventions are needed, thus guaranteeing money savings on management and
maintenance.
Compatibility:
Sadas Engine can be introduced with no effort into any data warehouse environment.
ADVANTAGES OF SADAS SOLUTION
STATISTICS FROM A DWH BUSINESS CASE
25
20
15
10
5
0
Loading
Time
Average
Inquiry
Time
Sadas Engine Other DBMS
Data Warehouse
0,03 sec
46
(�4,3TB)

More Related Content

What's hot

Data fabric and VMware
Data fabric and VMwareData fabric and VMware
Data fabric and VMware
VMware vFabric
 
Big Data Analytics Webinar
Big Data Analytics WebinarBig Data Analytics Webinar
Big Data Analytics Webinar
Eckerson Group
 
Keyrus US Information
Keyrus US InformationKeyrus US Information
Keyrus US Information
Julian Tong
 
Data Wearhouse (Dw) concepts
Data Wearhouse (Dw)  conceptsData Wearhouse (Dw)  concepts
Data Wearhouse (Dw) concepts
Being Topper
 
Real-Time Data Integration for Modern BI
Real-Time Data Integration for Modern BIReal-Time Data Integration for Modern BI
Real-Time Data Integration for Modern BI
ibi
 
Innovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud DetectionInnovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud Detection
DataStax
 
Business Intelligence - Intro
Business Intelligence - IntroBusiness Intelligence - Intro
Business Intelligence - Intro
David Hubbard
 
Data Virtualization for Compliance – Creating a Controlled Data Environment
Data Virtualization for Compliance – Creating a Controlled Data EnvironmentData Virtualization for Compliance – Creating a Controlled Data Environment
Data Virtualization for Compliance – Creating a Controlled Data Environment
Denodo
 
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
Denodo
 
Bi presentation to bkk
Bi presentation to bkkBi presentation to bkk
Bi presentation to bkk
guest4e975e2
 
Data-Ed Online Presents: Data Warehouse Strategies
Data-Ed Online Presents: Data Warehouse StrategiesData-Ed Online Presents: Data Warehouse Strategies
Data-Ed Online Presents: Data Warehouse Strategies
DATAVERSITY
 
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
Denodo
 
Top SAP Online training institute in Hyderabad
Top SAP Online training institute in HyderabadTop SAP Online training institute in Hyderabad
Top SAP Online training institute in Hyderabad
AadhyaKrishnan
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
VijayMohan Vasu
 
Data Warehouse Logical Design Guide
Data Warehouse Logical Design GuideData Warehouse Logical Design Guide
Data Warehouse Logical Design Guide
Andy Yuan
 
DATA MART APPROCHES TO ARCHITECTURE
DATA MART APPROCHES TO ARCHITECTUREDATA MART APPROCHES TO ARCHITECTURE
DATA MART APPROCHES TO ARCHITECTURE
Sachin Batham
 
Managing Smart Meter with DataStax DSE
Managing Smart Meter with DataStax DSEManaging Smart Meter with DataStax DSE
Managing Smart Meter with DataStax DSE
DataStax
 
Data Marketplace and the Role of Data Virtualization
Data Marketplace and the Role of Data VirtualizationData Marketplace and the Role of Data Virtualization
Data Marketplace and the Role of Data Virtualization
Denodo
 
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEEDTHE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
webwinkelvakdag
 
Benefits of a data warehouse presentation by Being topper
Benefits of a data warehouse presentation by Being topperBenefits of a data warehouse presentation by Being topper
Benefits of a data warehouse presentation by Being topper
Being Topper
 

What's hot (20)

Data fabric and VMware
Data fabric and VMwareData fabric and VMware
Data fabric and VMware
 
Big Data Analytics Webinar
Big Data Analytics WebinarBig Data Analytics Webinar
Big Data Analytics Webinar
 
Keyrus US Information
Keyrus US InformationKeyrus US Information
Keyrus US Information
 
Data Wearhouse (Dw) concepts
Data Wearhouse (Dw)  conceptsData Wearhouse (Dw)  concepts
Data Wearhouse (Dw) concepts
 
Real-Time Data Integration for Modern BI
Real-Time Data Integration for Modern BIReal-Time Data Integration for Modern BI
Real-Time Data Integration for Modern BI
 
Innovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud DetectionInnovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud Detection
 
Business Intelligence - Intro
Business Intelligence - IntroBusiness Intelligence - Intro
Business Intelligence - Intro
 
Data Virtualization for Compliance – Creating a Controlled Data Environment
Data Virtualization for Compliance – Creating a Controlled Data EnvironmentData Virtualization for Compliance – Creating a Controlled Data Environment
Data Virtualization for Compliance – Creating a Controlled Data Environment
 
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)
 
Bi presentation to bkk
Bi presentation to bkkBi presentation to bkk
Bi presentation to bkk
 
Data-Ed Online Presents: Data Warehouse Strategies
Data-Ed Online Presents: Data Warehouse StrategiesData-Ed Online Presents: Data Warehouse Strategies
Data-Ed Online Presents: Data Warehouse Strategies
 
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
Logical Data Fabric: Maturing Implementation from Small to Big (APAC)
 
Top SAP Online training institute in Hyderabad
Top SAP Online training institute in HyderabadTop SAP Online training institute in Hyderabad
Top SAP Online training institute in Hyderabad
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
 
Data Warehouse Logical Design Guide
Data Warehouse Logical Design GuideData Warehouse Logical Design Guide
Data Warehouse Logical Design Guide
 
DATA MART APPROCHES TO ARCHITECTURE
DATA MART APPROCHES TO ARCHITECTUREDATA MART APPROCHES TO ARCHITECTURE
DATA MART APPROCHES TO ARCHITECTURE
 
Managing Smart Meter with DataStax DSE
Managing Smart Meter with DataStax DSEManaging Smart Meter with DataStax DSE
Managing Smart Meter with DataStax DSE
 
Data Marketplace and the Role of Data Virtualization
Data Marketplace and the Role of Data VirtualizationData Marketplace and the Role of Data Virtualization
Data Marketplace and the Role of Data Virtualization
 
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEEDTHE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
 
Benefits of a data warehouse presentation by Being topper
Benefits of a data warehouse presentation by Being topperBenefits of a data warehouse presentation by Being topper
Benefits of a data warehouse presentation by Being topper
 

Similar to DWH: stop wasting time!

KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationKASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
Denodo
 
Neelesh it assignment
Neelesh it assignmentNeelesh it assignment
Neelesh it assignment
Neelesh Ganesh
 
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
 
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Denodo
 
Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)
Denodo
 
Data Analytics.pptx
Data Analytics.pptxData Analytics.pptx
Data Analytics.pptx
Rapyder Cloud Solutions
 
When and How Data Lakes Fit into a Modern Data Architecture
When and How Data Lakes Fit into a Modern Data ArchitectureWhen and How Data Lakes Fit into a Modern Data Architecture
When and How Data Lakes Fit into a Modern Data Architecture
DATAVERSITY
 
A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)
Denodo
 
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and TableauAnalyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
DATAVERSITY
 
Bridging the Last Mile: Getting Data to the People Who Need It
Bridging the Last Mile: Getting Data to the People Who Need ItBridging the Last Mile: Getting Data to the People Who Need It
Bridging the Last Mile: Getting Data to the People Who Need It
Denodo
 
The new EDW
The new EDWThe new EDW
The new EDW
Zac Brandt
 
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaIs your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Cloudera, Inc.
 
Data warehousing
Data warehousingData warehousing
Data warehousing
Juhi Mahajan
 
Exploiting Data Lakes: Architecture, Capabilities & Future
Exploiting Data Lakes: Architecture, Capabilities & FutureExploiting Data Lakes: Architecture, Capabilities & Future
Exploiting Data Lakes: Architecture, Capabilities & Future
Agilisium Consulting
 
What Does a Data Centre Do.docx
What Does a Data Centre Do.docxWhat Does a Data Centre Do.docx
What Does a Data Centre Do.docx
Gary Crilly, RCDD/OSP
 
The Smarter Way To Manage Data
The Smarter Way To Manage DataThe Smarter Way To Manage Data
The Smarter Way To Manage Data
Smart ERP Solutions, Inc.
 
Benefits of a data lake
Benefits of a data lake Benefits of a data lake
Benefits of a data lake
Sun Technologies
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
VijayMohan Vasu
 
Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.
Denodo
 
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
 

Similar to DWH: stop wasting time! (20)

KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationKASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
 
Neelesh it assignment
Neelesh it assignmentNeelesh it assignment
Neelesh it assignment
 
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
 
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
 
Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)
 
Data Analytics.pptx
Data Analytics.pptxData Analytics.pptx
Data Analytics.pptx
 
When and How Data Lakes Fit into a Modern Data Architecture
When and How Data Lakes Fit into a Modern Data ArchitectureWhen and How Data Lakes Fit into a Modern Data Architecture
When and How Data Lakes Fit into a Modern Data Architecture
 
A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)
 
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and TableauAnalyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
Analyzing Billions of Data Rows with Alteryx, Amazon Redshift, and Tableau
 
Bridging the Last Mile: Getting Data to the People Who Need It
Bridging the Last Mile: Getting Data to the People Who Need ItBridging the Last Mile: Getting Data to the People Who Need It
Bridging the Last Mile: Getting Data to the People Who Need It
 
The new EDW
The new EDWThe new EDW
The new EDW
 
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaIs your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
 
Data warehousing
Data warehousingData warehousing
Data warehousing
 
Exploiting Data Lakes: Architecture, Capabilities & Future
Exploiting Data Lakes: Architecture, Capabilities & FutureExploiting Data Lakes: Architecture, Capabilities & Future
Exploiting Data Lakes: Architecture, Capabilities & Future
 
What Does a Data Centre Do.docx
What Does a Data Centre Do.docxWhat Does a Data Centre Do.docx
What Does a Data Centre Do.docx
 
The Smarter Way To Manage Data
The Smarter Way To Manage DataThe Smarter Way To Manage Data
The Smarter Way To Manage Data
 
Benefits of a data lake
Benefits of a data lake Benefits of a data lake
Benefits of a data lake
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
 
Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.
 
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...
 

Recently uploaded

42 Ways to Generate Real Estate Leads - Sellxpert
42 Ways to Generate Real Estate Leads - Sellxpert42 Ways to Generate Real Estate Leads - Sellxpert
42 Ways to Generate Real Estate Leads - Sellxpert
vaishalijagtap12
 
Upturn India Technologies - Web development company in Nashik
Upturn India Technologies - Web development company in NashikUpturn India Technologies - Web development company in Nashik
Upturn India Technologies - Web development company in Nashik
Upturn India Technologies
 
Going AOT: Everything you need to know about GraalVM for Java applications
Going AOT: Everything you need to know about GraalVM for Java applicationsGoing AOT: Everything you need to know about GraalVM for Java applications
Going AOT: Everything you need to know about GraalVM for Java applications
Alina Yurenko
 
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Baha Majid
 
ppt on the brain chip neuralink.pptx
ppt  on   the brain  chip neuralink.pptxppt  on   the brain  chip neuralink.pptx
ppt on the brain chip neuralink.pptx
Reetu63
 
Software Test Automation - A Comprehensive Guide on Automated Testing.pdf
Software Test Automation - A Comprehensive Guide on Automated Testing.pdfSoftware Test Automation - A Comprehensive Guide on Automated Testing.pdf
Software Test Automation - A Comprehensive Guide on Automated Testing.pdf
kalichargn70th171
 
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
manji sharman06
 
What’s new in VictoriaMetrics - Q2 2024 Update
What’s new in VictoriaMetrics - Q2 2024 UpdateWhat’s new in VictoriaMetrics - Q2 2024 Update
What’s new in VictoriaMetrics - Q2 2024 Update
VictoriaMetrics
 
Superpower Your Apache Kafka Applications Development with Complementary Open...
Superpower Your Apache Kafka Applications Development with Complementary Open...Superpower Your Apache Kafka Applications Development with Complementary Open...
Superpower Your Apache Kafka Applications Development with Complementary Open...
Paul Brebner
 
Enhanced Screen Flows UI/UX using SLDS with Tom Kitt
Enhanced Screen Flows UI/UX using SLDS with Tom KittEnhanced Screen Flows UI/UX using SLDS with Tom Kitt
Enhanced Screen Flows UI/UX using SLDS with Tom Kitt
Peter Caitens
 
What’s New in VictoriaLogs - Q2 2024 Update
What’s New in VictoriaLogs - Q2 2024 UpdateWhat’s New in VictoriaLogs - Q2 2024 Update
What’s New in VictoriaLogs - Q2 2024 Update
VictoriaMetrics
 
Trailhead Talks_ Journey of an All-Star Ranger .pptx
Trailhead Talks_ Journey of an All-Star Ranger .pptxTrailhead Talks_ Journey of an All-Star Ranger .pptx
Trailhead Talks_ Journey of an All-Star Ranger .pptx
ImtiazBinMohiuddin
 
Folding Cheat Sheet #5 - fifth in a series
Folding Cheat Sheet #5 - fifth in a seriesFolding Cheat Sheet #5 - fifth in a series
Folding Cheat Sheet #5 - fifth in a series
Philip Schwarz
 
Secure-by-Design Using Hardware and Software Protection for FDA Compliance
Secure-by-Design Using Hardware and Software Protection for FDA ComplianceSecure-by-Design Using Hardware and Software Protection for FDA Compliance
Secure-by-Design Using Hardware and Software Protection for FDA Compliance
ICS
 
Hands-on with Apache Druid: Installation & Data Ingestion Steps
Hands-on with Apache Druid: Installation & Data Ingestion StepsHands-on with Apache Druid: Installation & Data Ingestion Steps
Hands-on with Apache Druid: Installation & Data Ingestion Steps
servicesNitor
 
ACE - Team 24 Wrapup event at ahmedabad.
ACE - Team 24 Wrapup event at ahmedabad.ACE - Team 24 Wrapup event at ahmedabad.
ACE - Team 24 Wrapup event at ahmedabad.
Maitrey Patel
 
What is Continuous Testing in DevOps - A Definitive Guide.pdf
What is Continuous Testing in DevOps - A Definitive Guide.pdfWhat is Continuous Testing in DevOps - A Definitive Guide.pdf
What is Continuous Testing in DevOps - A Definitive Guide.pdf
kalichargn70th171
 
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
kgyxske
 
TheFutureIsDynamic-BoxLang-CFCamp2024.pdf
TheFutureIsDynamic-BoxLang-CFCamp2024.pdfTheFutureIsDynamic-BoxLang-CFCamp2024.pdf
TheFutureIsDynamic-BoxLang-CFCamp2024.pdf
Ortus Solutions, Corp
 
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptxOperational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
sandeepmenon62
 

Recently uploaded (20)

42 Ways to Generate Real Estate Leads - Sellxpert
42 Ways to Generate Real Estate Leads - Sellxpert42 Ways to Generate Real Estate Leads - Sellxpert
42 Ways to Generate Real Estate Leads - Sellxpert
 
Upturn India Technologies - Web development company in Nashik
Upturn India Technologies - Web development company in NashikUpturn India Technologies - Web development company in Nashik
Upturn India Technologies - Web development company in Nashik
 
Going AOT: Everything you need to know about GraalVM for Java applications
Going AOT: Everything you need to know about GraalVM for Java applicationsGoing AOT: Everything you need to know about GraalVM for Java applications
Going AOT: Everything you need to know about GraalVM for Java applications
 
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
 
ppt on the brain chip neuralink.pptx
ppt  on   the brain  chip neuralink.pptxppt  on   the brain  chip neuralink.pptx
ppt on the brain chip neuralink.pptx
 
Software Test Automation - A Comprehensive Guide on Automated Testing.pdf
Software Test Automation - A Comprehensive Guide on Automated Testing.pdfSoftware Test Automation - A Comprehensive Guide on Automated Testing.pdf
Software Test Automation - A Comprehensive Guide on Automated Testing.pdf
 
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
Call Girls Bangalore🔥7023059433🔥Best Profile Escorts in Bangalore Available 24/7
 
What’s new in VictoriaMetrics - Q2 2024 Update
What’s new in VictoriaMetrics - Q2 2024 UpdateWhat’s new in VictoriaMetrics - Q2 2024 Update
What’s new in VictoriaMetrics - Q2 2024 Update
 
Superpower Your Apache Kafka Applications Development with Complementary Open...
Superpower Your Apache Kafka Applications Development with Complementary Open...Superpower Your Apache Kafka Applications Development with Complementary Open...
Superpower Your Apache Kafka Applications Development with Complementary Open...
 
Enhanced Screen Flows UI/UX using SLDS with Tom Kitt
Enhanced Screen Flows UI/UX using SLDS with Tom KittEnhanced Screen Flows UI/UX using SLDS with Tom Kitt
Enhanced Screen Flows UI/UX using SLDS with Tom Kitt
 
What’s New in VictoriaLogs - Q2 2024 Update
What’s New in VictoriaLogs - Q2 2024 UpdateWhat’s New in VictoriaLogs - Q2 2024 Update
What’s New in VictoriaLogs - Q2 2024 Update
 
Trailhead Talks_ Journey of an All-Star Ranger .pptx
Trailhead Talks_ Journey of an All-Star Ranger .pptxTrailhead Talks_ Journey of an All-Star Ranger .pptx
Trailhead Talks_ Journey of an All-Star Ranger .pptx
 
Folding Cheat Sheet #5 - fifth in a series
Folding Cheat Sheet #5 - fifth in a seriesFolding Cheat Sheet #5 - fifth in a series
Folding Cheat Sheet #5 - fifth in a series
 
Secure-by-Design Using Hardware and Software Protection for FDA Compliance
Secure-by-Design Using Hardware and Software Protection for FDA ComplianceSecure-by-Design Using Hardware and Software Protection for FDA Compliance
Secure-by-Design Using Hardware and Software Protection for FDA Compliance
 
Hands-on with Apache Druid: Installation & Data Ingestion Steps
Hands-on with Apache Druid: Installation & Data Ingestion StepsHands-on with Apache Druid: Installation & Data Ingestion Steps
Hands-on with Apache Druid: Installation & Data Ingestion Steps
 
ACE - Team 24 Wrapup event at ahmedabad.
ACE - Team 24 Wrapup event at ahmedabad.ACE - Team 24 Wrapup event at ahmedabad.
ACE - Team 24 Wrapup event at ahmedabad.
 
What is Continuous Testing in DevOps - A Definitive Guide.pdf
What is Continuous Testing in DevOps - A Definitive Guide.pdfWhat is Continuous Testing in DevOps - A Definitive Guide.pdf
What is Continuous Testing in DevOps - A Definitive Guide.pdf
 
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
一比一原版(sdsu毕业证书)圣地亚哥州立大学毕业证如何办理
 
TheFutureIsDynamic-BoxLang-CFCamp2024.pdf
TheFutureIsDynamic-BoxLang-CFCamp2024.pdfTheFutureIsDynamic-BoxLang-CFCamp2024.pdf
TheFutureIsDynamic-BoxLang-CFCamp2024.pdf
 
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptxOperational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
Operational ease MuleSoft and Salesforce Service Cloud Solution v1.0.pptx
 

DWH: stop wasting time!

  • 1. www.sadasengine.com Data Warehouse WHAT IS DWH? THE PROBLEM “A data warehouse is a copy of transaction data specifically structured for query and analysis.” “A subject oriented, integrated, time variant, and non-volatile collection of summary and detailed historical data used to support the strategic decision-making processes for the corporation.” “A data warehouse is the central storage point of all of the relevant information that is needed for BI reports.[…] a major part of the effort of creating a data warehouse is obtaining the big picture of what data exist, how is defined, and what the end result should look like.” “A data warehouse is a storage architecture designed to hold data extracted from transaction systems, operational data stores and external sources. The warehouse then combines that data in an aggregate, summary form suitable for enterprise-wide data analysis and reporting for predefined business needs.” Ralph Kimball William H. Inmon Chris Bradley Gartner Glossary Data Sources Data Acquisition Data Storage Data Analysis Reporting & Visualization Feeds (Rewrite, Append, Update) Streams Apps Source Systems OLTP, EDWFiles SQL ODBC JDBC SCI Multidimensional Analysis Data Mining Analytics Reporting ETL, Replication, Data Quality SQL, ODBC, JDBC, SCI • Multidimensional Analysis • Analytics Reporting • Data Mining ETL, Replication, Data Quality Feeds (Rewrite, Append, Update) A Data Warehouse essentially stores data, but there are also a lot of other activities it has to carry out: extract, transform and load data as well as retrieve and analyze it. This is necessary for business intelligence purposes in particular: retrieving and managing data effectively is crucial to gain useful information and allow for the best decision making. ETL time may be a pain point because the size of data is often huge. In fact, the quality of analysis depends on the volume of the information loaded in the data warehouse. On the other hand, query time is critical as well, especially for ad hoc analyses. Data Warehouse
  • 2. We provide software and services for data analysis in various and heterogeneous sectors, together with a range of cutting-edge Business Intelligence solutions. SADAS operates in many industries: banking, leasing, government, insurance, media & telco and retail. To know more about our products, visit our website www.sadasengine.com, or email us at sadasengine@sadasengine.com MILANO Headquarters Via Boschetti, 1 • 20121, Milano Tel: +39 02 29017449 ROMA Sales Management Via Principessa Clotilde, 7 • 00196, Roma Tel: +39 06 83089713 BATH Consulting & Training Services 1 Priory Close • Bath, BA2 5AL, UK Tel: +44 1225637004 SAN FRANCISCO USA International Office 20 California St. 7th floor • San Francisco, CA, 94111, USA Tel: +1 415 429 3969 NAPOLI Registered Offices, R&D, Customer Service Via Napoli, 159 • 80013, Casalnuovo di Napoli (NA) Tel: +39 081 8427112 / fax: +39 081 8427171 Our solution benefits from the characteristics of Sadas Engine, our flagship product: a columnar DBMS specifically designed to achieve outstanding performances in Data Warehouse environments. Sadas Engine is a revolutionary DBMS that meets companies’ needs in their daily activities of sourcing, analyzing and managing data. It is easy to integrate and very efficient in all ETL activities. Moreover, its front-end for dashboard & reporting works out-of-the-box. Columnar database efficient, fast, reliable and not expensive. Specific technology innovative indexes and structures, “Intelligent Upload” phase and “Learn by Usage”approach, i.e. capability to self adapt to new usage conditions. One stop shop all you need for data warehouse implementation, load and usage. Off-the-shelf hardware no need for expensive appliances or third party licenses. SADAS SOLUTION FOR DATA WAREHOUSING FEATURES & FUNCTIONS High Performances: the fastest and most efficient solution to ensure outstanding results on loading and analysis activities. Low TCO: running on low cost hardware & smart licensing allow Sadas to cut your TCO. Quick implementation: quick set-up process to save time, allowing for better design & analysis. Reduced maintenance cost: no DBA interventions are needed, thus guaranteeing money savings on management and maintenance. Compatibility: Sadas Engine can be introduced with no effort into any data warehouse environment. ADVANTAGES OF SADAS SOLUTION STATISTICS FROM A DWH BUSINESS CASE 25 20 15 10 5 0 Loading Time Average Inquiry Time Sadas Engine Other DBMS Data Warehouse 0,03 sec 46 (�4,3TB)