This document outlines the content of a 35-hour BI/BW course, including topics such as data warehousing concepts, SAP R/3 architecture, master data, transaction data, star schema concepts, BW architecture, reporting tools, data loading, scheduling data loads, variables, advanced modeling, ODS settings, data marts, extraction processes, roles, and transportation. The course appears to provide comprehensive coverage of the key concepts and components involved in business intelligence and data warehousing using SAP BW.
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.
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.
Srihitha Technologies provides Datastage Online Training in Ameerpet by real time Experts. For more information about Datastage online training in Ameerpet call 9885144200 / 9394799566.
Navigating the Transition from relational to NoSQL - CloudCon Expo 2012Dipti Borkar
For more deep NoSQL content from Couchbase, check out http://www.couchbase.com/webinars
NoSQL databases have emerged as a better match than relational systems for modern interactive applications, offering cost-effective data management at “Big Data” scale. But there are significant differences between structured and schema-less database technology. What should architects and technical managers know as they explore NoSQL solutions for their teams?
In this workshop you will learn:
- How to evaluate NoSQL (both technical advantages and limitations) as a potential data management approach
- Critical differences between NoSQL and RDBMS for designing, building and running production applications
- Ideal use cases for NoSQL technology and sample reference architectures
Loading a lot of data into a graph database is not a trivial exercise. TypeDB Loader (formerly known as GraMi) was developed to allow large-scale data import into TypeDB, a strongly-typed database. Recent improvements have immensely simplified the configuration interface to allow for easier data importing, while maintaining features and the promise of loading huge amounts of data into TypeDB as fast as possible.
This presentation will provide an overview on how reconciliation and/or validation rules can be defined and trial data can be checked against these rules. By utilizing JReview’s built-in browser and advanced functionalities, objects can be defined with drill-down capabilities to perform these data validation checks. For e.g. reconciliation checks between EDC data and external lab data can be easily performed by reviewing a summary object with discrepant information such as subject id, discrepancy category and discrepancy message with an ability to drill down to detailed discrepant data listings. This approach should support pro-active data management for ongoing trials increasing the overall data quality. Similar approach can be applied to review data against sponsor defined data standards checks.
Zeotap: Moving to ScyllaDB - A Graph of Billions ScaleSaurabh Verma
Zeotap’s Connect product addresses the challenges of identity resolution and linking for AdTech and MarTech. Zeotap manages roughly 20 billion ID and growing. In their presentation, Zeotap engineers will delve into data access patterns, processing and storage requirements to make a case for a graph-based store. They will share the results of PoCs made on technologies such as D-graph, OrientDB, Aeropike and Scylla, present the reasoning for selecting JanusGraph backed by Scylla, and take a deep dive into their data model architecture from the point of ingestion. Learn what is required for the production setup, configuration and performance tuning to manage data at this scale.
Zeotap: Moving to ScyllaDB - A Graph of Billions ScaleScyllaDB
Zeotap’s Connect product addresses the challenges of identity resolution and linking for AdTech and MarTech. Zeotap manages roughly 20 billion ID and growing. In their presentation, Zeotap engineers will delve into data access patterns, processing and storage requirements to make a case for a graph-based store. They will share the results of PoCs made on technologies such as D-graph, OrientDB, Aeropike and Scylla, present the reasoning for selecting JanusGraph backed by Scylla, and take a deep dive into their data model architecture from the point of ingestion. Learn what is required for the production setup, configuration and performance tuning to manage data at this scale.
Virtualizing Latency Sensitive Workloads and vFabric GemFireCarter Shanklin
This presentation was made by Emad Benjamin of VMware Technical Marketing. Normally I wouldn't upload someone else's preso but I really insisted this get posted and he asked me to help him out.
This deck covers tips and best practices for virtualizing latency sensitive apps on vSphere in general, and takes a deep dive into virtualizing vFabric GemFire, which is a high-performance distributed and memory-optimized key/value store.
Best practices include how to configure the virtual machines and how to tune them appropriately to the hardware the application runs on.
Ordex Presentation at Nationaal Congres Open Data Eindhoven 20 april 2012Tom Zeppenfeldt IEC MSc
Presentation by Tom Zeppenfeldt from Ophileon on the Open Reporting Data Exchange, a platform to share open data which is integrated with a monitoring and reporting tool.
Ordex serves as a source for open data for visualization
Srihitha Technologies provides Datastage Online Training in Ameerpet by real time Experts. For more information about Datastage online training in Ameerpet call 9885144200 / 9394799566.
Navigating the Transition from relational to NoSQL - CloudCon Expo 2012Dipti Borkar
For more deep NoSQL content from Couchbase, check out http://www.couchbase.com/webinars
NoSQL databases have emerged as a better match than relational systems for modern interactive applications, offering cost-effective data management at “Big Data” scale. But there are significant differences between structured and schema-less database technology. What should architects and technical managers know as they explore NoSQL solutions for their teams?
In this workshop you will learn:
- How to evaluate NoSQL (both technical advantages and limitations) as a potential data management approach
- Critical differences between NoSQL and RDBMS for designing, building and running production applications
- Ideal use cases for NoSQL technology and sample reference architectures
Loading a lot of data into a graph database is not a trivial exercise. TypeDB Loader (formerly known as GraMi) was developed to allow large-scale data import into TypeDB, a strongly-typed database. Recent improvements have immensely simplified the configuration interface to allow for easier data importing, while maintaining features and the promise of loading huge amounts of data into TypeDB as fast as possible.
This presentation will provide an overview on how reconciliation and/or validation rules can be defined and trial data can be checked against these rules. By utilizing JReview’s built-in browser and advanced functionalities, objects can be defined with drill-down capabilities to perform these data validation checks. For e.g. reconciliation checks between EDC data and external lab data can be easily performed by reviewing a summary object with discrepant information such as subject id, discrepancy category and discrepancy message with an ability to drill down to detailed discrepant data listings. This approach should support pro-active data management for ongoing trials increasing the overall data quality. Similar approach can be applied to review data against sponsor defined data standards checks.
Zeotap: Moving to ScyllaDB - A Graph of Billions ScaleSaurabh Verma
Zeotap’s Connect product addresses the challenges of identity resolution and linking for AdTech and MarTech. Zeotap manages roughly 20 billion ID and growing. In their presentation, Zeotap engineers will delve into data access patterns, processing and storage requirements to make a case for a graph-based store. They will share the results of PoCs made on technologies such as D-graph, OrientDB, Aeropike and Scylla, present the reasoning for selecting JanusGraph backed by Scylla, and take a deep dive into their data model architecture from the point of ingestion. Learn what is required for the production setup, configuration and performance tuning to manage data at this scale.
Zeotap: Moving to ScyllaDB - A Graph of Billions ScaleScyllaDB
Zeotap’s Connect product addresses the challenges of identity resolution and linking for AdTech and MarTech. Zeotap manages roughly 20 billion ID and growing. In their presentation, Zeotap engineers will delve into data access patterns, processing and storage requirements to make a case for a graph-based store. They will share the results of PoCs made on technologies such as D-graph, OrientDB, Aeropike and Scylla, present the reasoning for selecting JanusGraph backed by Scylla, and take a deep dive into their data model architecture from the point of ingestion. Learn what is required for the production setup, configuration and performance tuning to manage data at this scale.
Virtualizing Latency Sensitive Workloads and vFabric GemFireCarter Shanklin
This presentation was made by Emad Benjamin of VMware Technical Marketing. Normally I wouldn't upload someone else's preso but I really insisted this get posted and he asked me to help him out.
This deck covers tips and best practices for virtualizing latency sensitive apps on vSphere in general, and takes a deep dive into virtualizing vFabric GemFire, which is a high-performance distributed and memory-optimized key/value store.
Best practices include how to configure the virtual machines and how to tune them appropriately to the hardware the application runs on.
Ordex Presentation at Nationaal Congres Open Data Eindhoven 20 april 2012Tom Zeppenfeldt IEC MSc
Presentation by Tom Zeppenfeldt from Ophileon on the Open Reporting Data Exchange, a platform to share open data which is integrated with a monitoring and reporting tool.
Ordex serves as a source for open data for visualization
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
1. BI/BW Course Content
A Property of Choodamani Infotech
Duration: 35 Hrs Session: Weekdays/Weekends
Introduction Master Data
Ø Data ware Housing concepts Ø Attribute Data
Ø Overview of BI/BW Ø Text Data
Ø Overview of SAP R/3 Ø Hierarchy Data
Ø Types of Applications Ø Transaction Data
Ø OLTP Ø Header data
Ø OLAP Ø Item Data
Ø R/3 Architecture Ø Scheduling Data
Transportation Star Schema Concept
Ø Package Ø Classical Star Schema (DW)
Ø Request No Ø Extended star schema (BW)
Ø Return Codes
Naming Conversions
Ø (A,B..X & O) BW Architecture
Ø (Y & Z) PSA Maintenance
Types of Data Reporting
Ø Master Data Ø BEX Analyzer
Ø Transaction Data Ø BEX Browser
Ø WAD
Ø BEX Query designer
Data loading using flat file
Objects Ø Master data
Ø Info Area Ø Attribute data
Ø Info Object Catalog Ø Text Data
Ø Info Objects Ø Hierarchy data
Ø Info Source Ø Transaction Data
Ø Direct update Ø Reusability of Master data
Ø Flexible Update Ø Designing the transfer rules, transfer structure
Ø Data Source Ø Communication according to data using diff
Ø Source System Structure
Ø Application Component Ø Dynamic Calculation, Suppressing data,
Ø Transfer Rules Ø Adding new functionality to the data of transfer
Ø Transfer Structure rules
Ø Communication structure Ø Update rule level while loading data
Ø Info provider Ø Handling data function while loading data
Ø Data Targets
Ø Info Cubes
Ø ODS
Ø Update Rules
Ø Info package
2. BI/BW Course Content
A Property of Choodamani Infotech
Ø Extra Structure
Ø PSA
Scheduling the Data Variables
Ø Data Packet by data packet Ø Types
Ø Complete data scheduling Ø Represent
Ø Scheduling in background Ø Process
Ø Debugging the data while loading Ø Entry
Ø Transfer rule level Ø Conditions
Ø Update rule level Ø Formula
Ø PSA processing types Ø Calculated key figures, Restricted key figures
Ø Terminating errors while loading the Ø Exceptions
data Ø Filters
Ø Increasing the data packet size Ø Free characteristics
Ø Application server file concept – AL11 Ø Structures
Ø Scheduling the data in back ground Ø Cell Definition
Ø Monitoring the data loading Ø Query Performance
Ø Monitoring background jobs Ø Brain errors
Ø Scheduling jobs based on periodic values Ø Forcing variables
Ø Cancelling and deleting background jobs Ø Information broadcasting
Ø Cache monitoring
Ø RRI (Report to Report Interface)
Ø Attributes
Ø Navigational attributes
Ø Display attributes
Ø Query Properties
Ø Debugging reports while executing
Advance Modeling Role maintains
Ø ODS Ø Creating Role
Ø New data table Ø Assigning Role
Ø Active data table
Ø Change log table
ODS Setting Details
Ø Automatic Ø 9 cases of deltas with scenario
Ø Manual Ø Error handling details
Data mart Business Content
Ø ODS-to-Infocube Ø Definition
Ø Infocube to infocube Ø Activation
Ø ODS-ODS Ø Open hub services
Ø Multi providers Ø Info spoke
Ø Info set
Ø Partitioning Extraction
Ø Number range buffering Ø Flat file
Ø Line items dimension Ø LOS
Ø Currency conversion Ø LIS
Ø Performance issues Ø Generic Extraction
3. BI/BW Course Content
A Property of Choodamani Infotech
Ø Content Ø Master data
Ø Performance Ø Transaction data
Ø Request ID Ø CO-PA
Ø Aggregate Ø FI-SI
Ø Rollup & Collapse Ø DB connect
Ø Reconstruction Ø Business content extraction
Ø Deletion of data from data targets Ø Integration of RFC with R/3
Ø Complete deletion of data Ø Creating source site
Ø Deleting data by request id Ø Generic delta
Ø Selective deletion
Ø Process chain
Ø Meta chain
Ø Direct schedule
Ø Error handling in process chain
Ø Message integration
Ø Success
Ø Error
Ø Always
Ø Scheduling process chain based on
periodic values
Ø Cancelling the process chain jobs
Ø Rescheduling process chain job
Ø Folder creation for specific process chain
Ø Creating a variant for ABAP programs
and integrating in process chain
Ø ALE remote jobs
Ø Attribute change run
Ø Transportation
Ø Assigning object to requests
Ø Releasing request number and their
dependency
Ø Return code
Ø Mail drafting to basis team regarding
transportation
Ø Searching objects locally and business
Ø Content through metadata repository
Ø SQVI-Quick Views
Ø Info set editing