Macsteel Service Centers USA is a leading metals processor and distributor with over 30 locations across North America. The company implemented Oracle E-Business Suite for financials, order management, manufacturing, and other functions. It developed a data warehouse using Oracle Analytics Cloud and Informatica to integrate data from various systems and provide self-service analytics and reporting. This improved decision making and user satisfaction while reducing IT costs compared to a custom data warehouse. Lessons included focusing user requirements on abilities rather than reports and fine-tuning data extraction layers.
This presenation explains basics of ETL (Extract-Transform-Load) concept in relation to such data solutions as data warehousing, data migration, or data integration. CloverETL is presented closely as an example of enterprise ETL tool. It also covers typical phases of data integration projects.
This presenation explains basics of ETL (Extract-Transform-Load) concept in relation to such data solutions as data warehousing, data migration, or data integration. CloverETL is presented closely as an example of enterprise ETL tool. It also covers typical phases of data integration projects.
It is an Comprehensive ETL Tool, Which provides, end to end ERP Solutions,Some of the Most popular ETL Tools are DSPX leader of ETL Tools, Started from 2006,Informatics,ODI,SAS (ETL STUDIO),BODI,ABNITRO.
For More Follow Below Link:
http://bit.ly/1zMzPjW
After completing this module, you will be able to:
List and describe the major components of the Teradata architecture.
Describe how the components interact to manage incoming and outgoing data.
List 5 types of Teradata database objects.
Teradata Technology Leadership and InnovationTeradata
Teradata is the world's leader in data warehousing and integrated marketing management through its database software, data warehouse appliances, and enterprise analytics. For more information, visit teradata.com.
Data Warehouse:
A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format.
Reconciled data: detailed, current data intended to be the single, authoritative source for all decision support.
Extraction:
The Extract step covers the data extraction from the source system and makes it accessible for further processing. The main objective of the extract step is to retrieve all the required data from the source system with as little resources as possible.
Data Transformation:
Data transformation is the component of data reconcilation that converts data from the format of the source operational systems to the format of enterprise data warehouse.
Data Loading:
During the load step, it is necessary to ensure that the load is performed correctly and with as little resources as possible. The target of the Load process is often a database. In order to make the load process efficient, it is helpful to disable any constraints and indexes before the load and enable them back only after the load completes. The referential integrity needs to be maintained by ETL tool to ensure consistency.
This document describes the overview of SAP BusinessObjects Rapid Marts, available Rapid Mart
packages, how Rapid Mart packages helps and accelerates in Data Warehouse implementation process
What is Data Warehousing? ,
Who needs Data Warehousing? ,
Why Data Warehouse is required? ,
Types of Systems ,
OLTP
OLAP
Maintenance of Data Warehouse
Data Warehousing Life Cycle
Datawa.re: Data warehouse design, development and support just got alot fasterJohn Leonard
Datawa.re Dynamic Warehouse Automation Platform products and services accelerate the time-to-value so you can make more informed business decisions faster... and respond more quickly when the business environment changes. Datawa.re automates the design, build, and ongoing operations, accelerating the development and implementation, and retaining flexibility... all while reducing the required resources. Our table-driven approach enables better collaboration across business and information technology teams... reducing project cost and risk.
It is an Comprehensive ETL Tool, Which provides, end to end ERP Solutions,Some of the Most popular ETL Tools are DSPX leader of ETL Tools, Started from 2006,Informatics,ODI,SAS (ETL STUDIO),BODI,ABNITRO.
For More Follow Below Link:
http://bit.ly/1zMzPjW
After completing this module, you will be able to:
List and describe the major components of the Teradata architecture.
Describe how the components interact to manage incoming and outgoing data.
List 5 types of Teradata database objects.
Teradata Technology Leadership and InnovationTeradata
Teradata is the world's leader in data warehousing and integrated marketing management through its database software, data warehouse appliances, and enterprise analytics. For more information, visit teradata.com.
Data Warehouse:
A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format.
Reconciled data: detailed, current data intended to be the single, authoritative source for all decision support.
Extraction:
The Extract step covers the data extraction from the source system and makes it accessible for further processing. The main objective of the extract step is to retrieve all the required data from the source system with as little resources as possible.
Data Transformation:
Data transformation is the component of data reconcilation that converts data from the format of the source operational systems to the format of enterprise data warehouse.
Data Loading:
During the load step, it is necessary to ensure that the load is performed correctly and with as little resources as possible. The target of the Load process is often a database. In order to make the load process efficient, it is helpful to disable any constraints and indexes before the load and enable them back only after the load completes. The referential integrity needs to be maintained by ETL tool to ensure consistency.
This document describes the overview of SAP BusinessObjects Rapid Marts, available Rapid Mart
packages, how Rapid Mart packages helps and accelerates in Data Warehouse implementation process
What is Data Warehousing? ,
Who needs Data Warehousing? ,
Why Data Warehouse is required? ,
Types of Systems ,
OLTP
OLAP
Maintenance of Data Warehouse
Data Warehousing Life Cycle
Datawa.re: Data warehouse design, development and support just got alot fasterJohn Leonard
Datawa.re Dynamic Warehouse Automation Platform products and services accelerate the time-to-value so you can make more informed business decisions faster... and respond more quickly when the business environment changes. Datawa.re automates the design, build, and ongoing operations, accelerating the development and implementation, and retaining flexibility... all while reducing the required resources. Our table-driven approach enables better collaboration across business and information technology teams... reducing project cost and risk.
Support de formation pour les ateliers menés à l'atelier Canopé 90 Belfort pour la journée des Professeurs Documentalistes du Nord Franche-Comté #jdoc90.
Oracle's Exadata Database Machine has accomplished huge early reception and acknowledgment of its database appliance value proposition. It’s assessed that nearly 400 clients have conveyed Oracle Exadata, research report also depicts its consistent progress at the time of change. Here is Exadata Experiences by Expert & Customer Panel.
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Delta Lake OSS: Create reliable and performant Data Lake by Quentin AmbardParis Data Engineers !
Delta Lake is an open source framework living on top of parquet in your data lake to provide Reliability and performances. It has been open-sourced by Databricks this year and is gaining traction to become the defacto delta lake format.
We’ll see all the goods Delta Lake can do to your data with ACID transactions, DDL operations, Schema enforcement, batch and stream support etc !
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage like a kid in a candy store? We’ll discuss what platforms to use for what data. This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.
Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions amidst this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2020 and beyond for success.
Today, many businesses around the world are using an Oracle product and in many of these at the core there is an Oracle Database. Many of us who started as a Database administrator where put in this position because we were good PL/SQL programmers or good Sysadmins, but knew very little of what it took to be a DBA. In this session you will learn the core architecture of an Oracle Database in 12c as well as what it takes to administer and apply this new knowledge the day you go back to your office.
ADV Slides: When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Webinar future dataintegration-datamesh-and-goldengatekafkaJeffrey T. Pollock
The Future of Data Integration: Data Mesh, and a Special Deep Dive into Stream Processing with GoldenGate, Apache Kafka and Apache Spark. This video is a replay of a Live Webinar hosted on 03/19/2020.
Join us for a timely 45min webinar to see our take on the future of Data Integration. As the global industry shift towards the “Fourth Industrial Revolution” continues, outmoded styles of centralized batch processing and ETL tooling continue to be replaced by realtime, streaming, microservices and distributed data architecture patterns.
This webinar will start with a brief look at the macro-trends happening around distributed data management and how that affects Data Integration. Next, we’ll discuss the event-driven integrations provided by GoldenGate Big Data, and continue with a deep-dive into some essential patterns we see when replicating Database change events into Apache Kafka. In this deep-dive we will explain how to effectively deal with issues like Transaction Consistency, Table/Topic Mappings, managing the DB Change Stream, and various Deployment Topologies to consider. Finally, we’ll wrap up with a brief look into how Stream Processing will help to empower modern Data Integration by supplying realtime data transformations, time-series analytics, and embedded Machine Learning from within data pipelines.
GoldenGate: https://www.oracle.com/middleware/tec...
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
Oracle R12 OBIEE, Better Decisions Faster with Advanced Analytics
1. Stuart Patsos, CIO / VP of IT
Better Decisions Faster with Advanced Analytics
2. Company Background
Macsteel Service Centers USA is one of the leading metals
processors and distributors in North America. March 1, Kloeckner
Metals US.
A division of Kloeckner & Co – the largest mill-independent
distributor of steel in the world
● 30+ locations throughout North America and Puerto Rico
● processes and distributes
► carbon ► aluminum
► stainless ► specialty metals
● Products include a full range of
► flat rolled ► pipe
► plate ► bar
► tubing ► structurals
● The company also supplies a full range of
► Coated ► steel building products
► prepainted metals
2
2
3. Applications Footprint
Version of EBS currently Implemented: 12.1.2
Oracle products implemented:
Financials (GL, AP, AR, Advanced Collections)
Order Management (including Configurator)
OPM (Process Manufacturing)
Discrete Manufacturing
Inventory
Procurement (including LCM – Landed Cost Management)
OTM (version 6.04)
eBusiness Tax (with Vertex O series)
OBIEE and OBIEA
On Demand since Sept 20, 2010
Future implementation
Warehouse Management
EAM
ASCP
3
4. Macsteel Design Guidelines
Developed with a standard approach
Follow Oracle Data Warehouse approach
Keep with standard and common technologies
Design your system for data analysis not for technology
Simplify the design – make reporting user driven
Let the business drive your data model not the technology
Develop a flexible system
Simple data warehouse design and standard technologies
• will lower the cost of warehouse maintenance
• This allows IT to respond to business requirement changes
Keep the data transformation as simple as possible
4
5. Macsteel Data Warehouse
Data
Oracle Main data
Other Files EBS Source
Syste
Data Dashboard
ms
The
presentation
layer can be
Informatica changed to
Mapping your system
Tool of choice
I
N Adhoc
F
ETL
O Reports
R
M
OBIEE
A This tool
T allows the end
DAC users to
I
maintain
C rollups and
A hierarchies in Prebuilt
the data
Informatica
warehouse Reports
Data
DW DDM (3rd party)
Warehouse
Administration Dimension Data
Console Manager
5
6. Macsteel Data Warehouse
Oracle Delivered Data Warehouse
Oracle Financials Analytics
Oracle Transportation Management (Transportation Analytics)
Oracle Procurement & Spend Analytics
Oracle Supply Chain Analytics
Macsteel Enhancement to Oracle Delivered data warehouse
Custom Branch security
Custom Hierarchy and Rollup Management
Dimensional Data Management
Macsteel Custom Data Warehouse
Custom Manufacturing Data Mart
Custom Revenue and Cost of Goods Sold Data Mart
Custom Inventory Data Warehouse needed for Macsteel requirements
Consolidated Data Warehouse to join key data of the two US operating
companies
6
7. Why We Chose Oracle Analytics
Oracle prebuilt data warehouse eliminates the risk associated with custom data
warehouse
Oracle delivered data warehouse has been engineered with the latest methodologies
in data warehousing. This enabled our organization to follow the same guidelines
when building our additional data warehouse needs
Keep with standard and common technologies – Easier to design a system and
anticipate potential problems
Lower the reliance on internal employee who have designed the custom data
warehouse
Faster go-live with Oracle delivered data warehouse
Lower the resource cost when upgrading Oracle Applications. Oracle delivered data
warehouse will provide an upgrade path to stay current with new data models
Pre-delivered reports and dashboards will reduce report development time and
increase data accuracy
Implementing Oracle delivered data warehouse allowed us to easily move our data
warehouse to Oracle On Demand
7
8. Results Achieved by Macsteel
For Users
Increased user satisfaction with better reporting
Self Service reporting allows the users to get the data when they need it
Better decision making
Self Service executive dashboard
For Information Technology
Lower the cost of the ownership
Reduced the technical development effort
Reduced report development in EBS
Reduced load on production systems
Taking advantage of Oracle standardized technologies stack
Using Oracle Standard for all non Oracle Data Warehouse needs
Easier to find technical resources for Oracle Data Warehouse
8
9. Lessons Learned
Expect to see holes in your processes
• Be prepared to do some change management after seeing
the results of OBIEE – don’t get caught off guard by this
Defining clear user requirements is important, but do not focus
the requirements on report design, focus the requirements on
abilities. For example
• “I need the ability to see my spend by supplier, by
commodity, year over year”
• NOT ‘Row1, row1, row3, using parameters x, y, and z and
filters a, b.
The connectors and extract layers are extremely valuable, but
expect some fine tuning for it to fit your data and processes.
May need to extend or build new data transportation layers
9