Wallchart - Data Warehouse Documentation RoadmapDavid Walker
All projects need documentation and many companies provide templates as part of a methodology. This document describes the templates, tools and source documents used by Data Management & Warehousing. It serves two purposes:
• For projects using other methodologies or creating their own set of documents to use as a checklist. This allows the project to ensure that the documentation covers the essential areas for describing the data warehouse.
• To demonstrate our approach to our clients by describing the templates and deliverables that are produced.
Documentation, methodologies and templates are inherently both incomplete and flexible. Projects may wish to add, change, remove or ignore any part of any document. Some may also believe that aspects of one document would sit better in another. If this is the case then users of this document and these templates are encouraged to change them to fit their needs.
Data Management & Warehousing believes that the approach or methodology for building a data warehouse should be to use a series of guides and checklists. This ensures that small teams of relatively skilled resources developing the system can cover all aspects of the project whilst being free to deal with the specific issues of their environment to deliver exceptional solutions, rather than a rigid methodology that ensures that large teams of relatively unskilled staff can meet a minimum standard.
Wallchart - Data Warehouse Documentation RoadmapDavid Walker
All projects need documentation and many companies provide templates as part of a methodology. This document describes the templates, tools and source documents used by Data Management & Warehousing. It serves two purposes:
• For projects using other methodologies or creating their own set of documents to use as a checklist. This allows the project to ensure that the documentation covers the essential areas for describing the data warehouse.
• To demonstrate our approach to our clients by describing the templates and deliverables that are produced.
Documentation, methodologies and templates are inherently both incomplete and flexible. Projects may wish to add, change, remove or ignore any part of any document. Some may also believe that aspects of one document would sit better in another. If this is the case then users of this document and these templates are encouraged to change them to fit their needs.
Data Management & Warehousing believes that the approach or methodology for building a data warehouse should be to use a series of guides and checklists. This ensures that small teams of relatively skilled resources developing the system can cover all aspects of the project whilst being free to deal with the specific issues of their environment to deliver exceptional solutions, rather than a rigid methodology that ensures that large teams of relatively unskilled staff can meet a minimum standard.
Pivotal CRM Services offers the CDC Software Data Archiving solution that streamlines your data management operations and ensures continued, long-term, secure access to your archives
Geometric provides an intelligent approach to the migration of the PDM data in the context of applications and processes by assisting the customer in planning, assessment and suggesting right migration approach.
Microsoft SQL Server - How to Collaboratively Manage Excel DataMark Ginnebaugh
How to Collaboratively Manage Excel-Based Process Data in SQL Server
Your organization probably uses Excel for a variety of business processes including budgeting, sales revenue forecasting, product demand planning, and project management.
You'll learn how to set up and manage multi-user collaborative processes using Excel as the data form and SQL Server as the data store and process engine.
You'll learn:
* How to enable cell-level collaboration between multiple users using Excel and SQL Server.
* How to effectively integrate desktop Excel-based process data with enterprise applications.
* How to mitigate the limitations normally associated with Excel-to-database connections including record locking (check-in/out), conflict management, and change management and versioning.
Case Study: Using SAP to Streamline Operations of a ManufacturerAndrew Ho
A case study following Crestron's initial decision to implement SAP R/3 as its Enterprise Resource Planning (ERP) system through more recent upgrades, with BearingPoint's help, to implement further process improvements.
Database Architechs is a database-focused consulting company for 17 years bringing you the most skilled and experienced data and database experts with a wide variety of service offering covering all database and data related aspects.
Presented at the Halifax State of the Economy Conference 2012
Russell Riblett from GIS Planning presented the different marketing strategies economic development organizations and community marketers employ and which methods are most effective. It included the business site location process and the sources corporate real estate professionals use, as well as how marketing has changed from the past to the present and the direction it will move in the future addressing these marketing questions:
1. What is most effective?
2. Where should you invest your marketing dollars?
3. How are site selectors making decisions?
4. What does not work anymore?
5. What does the future look like?
6. What information really matters?
7. How can you be successful?
Pivotal CRM Services offers the CDC Software Data Archiving solution that streamlines your data management operations and ensures continued, long-term, secure access to your archives
Geometric provides an intelligent approach to the migration of the PDM data in the context of applications and processes by assisting the customer in planning, assessment and suggesting right migration approach.
Microsoft SQL Server - How to Collaboratively Manage Excel DataMark Ginnebaugh
How to Collaboratively Manage Excel-Based Process Data in SQL Server
Your organization probably uses Excel for a variety of business processes including budgeting, sales revenue forecasting, product demand planning, and project management.
You'll learn how to set up and manage multi-user collaborative processes using Excel as the data form and SQL Server as the data store and process engine.
You'll learn:
* How to enable cell-level collaboration between multiple users using Excel and SQL Server.
* How to effectively integrate desktop Excel-based process data with enterprise applications.
* How to mitigate the limitations normally associated with Excel-to-database connections including record locking (check-in/out), conflict management, and change management and versioning.
Case Study: Using SAP to Streamline Operations of a ManufacturerAndrew Ho
A case study following Crestron's initial decision to implement SAP R/3 as its Enterprise Resource Planning (ERP) system through more recent upgrades, with BearingPoint's help, to implement further process improvements.
Database Architechs is a database-focused consulting company for 17 years bringing you the most skilled and experienced data and database experts with a wide variety of service offering covering all database and data related aspects.
Presented at the Halifax State of the Economy Conference 2012
Russell Riblett from GIS Planning presented the different marketing strategies economic development organizations and community marketers employ and which methods are most effective. It included the business site location process and the sources corporate real estate professionals use, as well as how marketing has changed from the past to the present and the direction it will move in the future addressing these marketing questions:
1. What is most effective?
2. Where should you invest your marketing dollars?
3. How are site selectors making decisions?
4. What does not work anymore?
5. What does the future look like?
6. What information really matters?
7. How can you be successful?
The CityMatters survey asks citizens what it's really like to live in Halifax and how they feel about our economy, lifestyle, government and more. This presentation was prepared by Rick Emberley, Senior Council for MQO Research highlighting the results of the survey. There was an interactive panel discussion which took place on December 1, 2014 at the Prince George Hotel.
Halifax State of the Economy Conference 2012
The 1st Halifax Index was launched at the conference. It tells Halifax's city’s story - the strength of the economy, the health of the community, the sustainability of the environment and the progress of the Economic Strategy.
It’s a new and innovative way to measure progress that reaches beyond traditional economic indicators like GDP and jobs.
Download the complete Index at www.halifaxindex.com
The work pressures, the work culture, timings, appraisals make the young executives very vulnerable for mental health issues. I had put together a presentation for a seminar.
Plan Amsterdam, over de brettenzone en Sloterdijk met onze bijdrage!Wouter Valkenier
In het eerste artikel, een nadere kennismaking met
de verschillende deelgebieden Sloterdijk I, II, III, IV en
Sloterdijk Centrum, ofwel de Sloterdijken. Daarna meer
over de oorzaken voor de hernieuwde dynamiek in
het gebied. In het tweede artikel wordt dieper ingegaan
op de nieuwe woonfunctie in Sloterdijk Centrum,
het kantorengebied rond station Sloterdijk. Waarom
mag het nu wel? Waar mogen mensen precies wonen.
En, hoe gaat de gemeente dit aanpakken?
Het derde artikel gaat over het groen. Elke Amsterdammer
heeft groen op loop- en fietsafstand. Zo ook
de nieuwe bewoners. De Bretten is een natuurgebied
dat deels is aangelegd, maar grotendeels zelf is ontstaan.
Een relatief onbekend juweeltje, maar ook daar zal
vanzelf verandering in komen. Er is gewoonweg veel
te zien en te beleven voor de Amsterdammer.
A National Management Plan for a protected non-timber CITES listed tree speci...Verina Ingram
A National Management Plan for a protected non-timber CITEs listed tree species: Prunus africana. Ingram et al. pygeum mgt plan presentation nat forum march 10
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...ScyllaDB
Discover how to avoid common pitfalls when shifting to an event-driven architecture (EDA) in order to boost system recovery and scalability. We cover Kafka Schema Registry, in-broker transformations, event sourcing, and more.
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Denodo
Watch full webinar here: https://bit.ly/34iCruM
Many organizations are embarking on strategically important journeys to embrace data and analytics. The goal can be to improve internal efficiencies, improve the customer experience, drive new business models and revenue streams, or – in the public sector – provide better services. All of these goals require empowering employees to act on data and analytics and to make data-driven decisions. However, getting data – the right data at the right time – to these employees is a huge challenge and traditional technologies and data architectures are simply not up to this task. This webinar will look at how organizations are using Data Virtualization to quickly and efficiently get data to the people that need it.
Attend this session to learn:
- The challenges organizations face when trying to get data to the business users in a timely manner
- How Data Virtualization can accelerate time-to-value for an organization’s data assets
- Examples of leading companies that used data virtualization to get the right data to the users at the right time
Data Virtualization for Data Architects (New Zealand)Denodo
Watch full webinar here: https://bit.ly/3ogCJKC
Success or failure in the digital age will be determined by how effectively organisations manage their data. The speed, diversity and volume of data present today can overwhelm older data architectures, leaving business leaders lacking the insight and operational agility needed to respond to market opportunity or competitive challenges.
With the pace of today’s business, modernisation of a data architecture must be seamless, and ideally, built on existing capabilities. This webinar explores how data virtualization can help provide a seamless evolution to the capabilities of an existing data architecture without business disruption.
You will discover:
How to modernise your data architectures without disturbing the existing analytical workload
- How to extend your data architecture to more quickly exploit existing, and new sources of data
- How to enable your data architecture to present more low latency data
How we evolved data pipeline at Celtra and what we learned along the wayGrega Kespret
Presented at Data Science Meetup on 4/12/2018.
In this talk, Grega Kespret (head of analytics group) will present Celtra’s data analytics pipeline and how it evolved through the years - sometimes forward, sometimes backward. On this journey, we became early adopter of different technologies: BigQuery, Vertica (pre-join projections), Spark (version 0.5), Databricks (beta users) and Snowflake (one of the first users). As the business grew and the product evolved, volume and complexity of data increased ten-fold, as has the number of users generating insights from this data. How come BigQuery did not scale? Why was choosing Vertica a mistake for our use case, and what have we learned from it? What requirements did we have for the analytics database, why did we have to abandon MySQL, and why we finally chose Snowflake? This talk will be heavily opinionated and will describe our experience and learnings - what worked for us and what didn't.
Introduction to Modern Data Virtualization 2021 (APAC)Denodo
Watch full webinar here: https://bit.ly/2XXyc3R
“Through 2022, 60% of all organisations will implement data virtualization as one key delivery style in their data integration architecture," according to Gartner. What is data virtualization and why is its adoption growing so quickly? Modern data virtualization accelerates that time to insights and data services without copying or moving data.
Watch on-demand this webinar to learn:
- Why organizations across the world are adopting data virtualization
- What is modern data virtualization
- How data virtualization works and how it compares to alternative approaches to data integration and management
- How modern data virtualization can significantly increase agility while reducing costs
ADV Slides: Comparing the Enterprise Analytic SolutionsDATAVERSITY
Data is the foundation of any meaningful corporate initiative. Fully master the necessary data, and you’re more than halfway to success. That’s why leverageable (i.e., multiple use) artifacts of the enterprise data environment are so critical to enterprise success.
Build them once (keep them updated), and use again many, many times for many and diverse ends. The data warehouse remains focused strongly on this goal. And that may be why, nearly 40 years after the first database was labeled a “data warehouse,” analytic database products still target the data warehouse.
Self-serve analytics journey at Celtra: Snowflake, Spark, and DatabricksGrega Kespret
Celtra provides a platform for streamlined ad creation and campaign management used by customers including Porsche, Taco Bell, and Fox to create, track, and analyze their digital display advertising. Celtra’s platform processes billions of ad events daily to give analysts fast and easy access to reports and ad hoc analytics. Celtra’s Grega Kešpret leads a technical dive into Celtra’s data-pipeline challenges and explains how it solved them by combining Snowflake’s cloud data warehouse with Spark to get the best of both.
Topics include:
- Why Celtra changed its pipeline, materializing session representations to eliminate the need to rerun its pipeline
- How and why it decided to use Snowflake rather than an alternative data warehouse or a home-grown custom solution
- How Snowflake complemented the existing Spark environment with the ability to store and analyze deeply nested data with full consistency
- How Snowflake + Spark enables production and ad hoc analytics on a single repository of data
Exploring Neo4j Graph Database as a Fast Data Access LayerSambit Banerjee
This article describes the findings of an extensive investigative work conducted to explore the feasibility of using a Neo4j Graph Database to build a Fast Data Access Layer with near-real time data ingestion from the underlying source systems.
Jacobs has used Endeavour (AVEVA NET) for more than 12 years for delivery of project data. The use has been primarily driven by customer or contract requirements for data handover, but over time both Jacobs’ project teams and customers have recognized the value of having trustworthy and complete data at the completion of a project, and is giving a focused effort to execute data-centric projects moving forward. To support this, Jacobs is implementing AVEVA Engineering to drive a data-centric collaboration between disciplines to enable greater work efficiencies. This game-changing approach using Endeavour and AVEVA Engineering will provide data alignment across the full project spectrum of EPC delivery.
Presented by: Marc-Henri Cerar—Jacobs
Discover how AVEVA can transform your business today
www.aveva.com
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Basic phrases for greeting and assisting costumers
Gic2011 aula3-ingles
1. Information & Knowledge
Management - Class 3
Marielba Zacarias
Prof. Auxiliar DEEI
FCT I, Gab 2.69, Ext. 7749
Data-warehousing
mzacaria@ualg.pt
http://w3.ualg.pt/~mzacaria
3. Data Warehousing
Data collection for analysis and
reporting taks
Historical data
Stored in a distinct environment from
operational data
Structure different from data-bases
4. Why
Operational and analitical data have
different requirements in terms of
usage (frequency, response time)
hardware
software
structure
7. The “arquitected” environment”
Atomic Dept. individual
operational
dw dw dw
“data-marts”
Detailed temporal
More granular derived,
daily Ad-hoc
Temporal Some primitive
current value Heuristic
Integrated Typical of Marketing
High access prob. Não-repetitive
Subject oriented Engineering
Application oriented Oriented to PC or
Sumarized Production
workstations
Accounting
7
8. Type of questions
Atomico
operacional Dept. individual
dw
J. Jones 1986-87
Jan – 4101 Clientes
123 Main St. J. Jones
Fev – 4209 Desde 1982
Credit - AA 456 High St.
Mar- 4175 Com saldos
Credit - B
Apr - 4215 > 5,000
Jones e crédito
Credit? 1987-89
Monthly >= B
J. Jones
456 High St. Sales?
Credit - A
1989 – pte. Client types
Jones J. Jones in analysis?
Credit 123 Main St.
History? Credit - AA
8
9. Architected Environment
Production
Environment
Operational Analitical
environment Environment
9
10. Data-warehouse design
Requirement Performance Tuning
Gatherings Query
Physical Optimization
Environment Setup Quality Assurance
Data Modeling Rolling out to
ETL Production
OLAP Cube Design Production
Front End Maintenance
Development Incremental
Enhancements
Report
Development
11. Requirements
Gathering
Take into account users
Executive with little time and knowledge about
technical terms
Interviews, JAD sessions
User Reporting/Analysis Requirements
Hardware, training requirements
Data source identification
Concrete project plan
12. Physical Environment
Setup
Setup Servers, DBMS and databases,
ETL, OLAP Cubes and reporting services
Create three environments
development, testing, production
13. Data-modeling
Depends on initial data source identification
Conceptual, logical and physical data modeling
Should be related
to the information
architecture!!!!
14. Data Modeling
Dimensional Approach
Transactional data is partitioned in facts
Numeric transaction data
products ordered, price
Dimensions
provide context for facts
order date, customer name, product
number, location info, salesperson
15. Dimensional Approaches
Star
Fact table (typically a transaction)
Dimensions (context of the transaction)
Snowflake
Dimensions indirectly linked to fact
tables
21. OLAP Cube Design
Specification of detailed reporting needs
in terms of the multi-dimensional
structure previously defined (star or
snowflake), but regarded as a n-
dimensional cube
star/snowflake and cubes are pretty
much the same thing
cubes are more appropriate for not IT
users
29. SQL Server
Integration Examples II
Qualitative data
Description term ActionId
team meeting 18
hr distribution 19
project list 19
team meeting 19
hr distribution 26
project list 26
claims application 27
claims application 28
cards application maintenance 29
claims application integration 30
hr distribution 31
project list 31
claims application 34
claims application 35
hr distribution 36
project list 36
31. Front-end development
Front-ends range from
in-house development with scripting
languages php, asp, or perl
to off-the-shelf products such as Crystal
Reports or higher-end products such as
Actuate
OLAP vendors also offer front-ends of their
own
32. Report Development
Derived from requirements
Main point of contact between the data-
warehouse and users
User customization
Report Delivery (web, e-mail, sms, file
formats)
Access privileges
34. Query Optimization
Understand how your DBMS executes queries
Store intermediate results in temporary tables
Query Optimization tips
Use indexes
Partition tables (vertically and horizontally)
De-normalize (less joins)
Server Tuning
35. Quality Assurance
Test plan with quality criteria for data
Critical success factor
Often overlooked
Performed by people with knowledge of
the business data not data-warehouses
Resistance
36. Rolling to production
Seems easy but..
Putting everyone online may take a full
week in some cases
Online access can be as simple as
sending a link by e-mail
37. Production Maintenance
Backup and recovery processes
Crisis Management
Monitoring end-user usage
Capture runaways queries before
whole system is slowed down
To measure usage for ROI calculations
and future enhancements
38. Incremental enhancements
Accomplish small changes such as
changing original geographical
designations
A company may add new sales regions
No matter how simple, never do them
directly in production environment
43. Tools for unstructured
information management
Content Management Systems
Record Management Systems
Digital Image Management Systems
Digital Asset Management Systems
Digital Imaging Systems
