SISG provides business intelligence, data warehousing, and data integration solutions. They utilize agile project methodology and virtual environments to iteratively deliver customized data solutions. Their services include strategic planning, project management, data modeling, extraction and loading, and infrastructure optimization. SISG focuses exclusively on these niche areas and aims to provide high value solutions through their expertise and productivity tools.
Chief Data Officer (CDO) Organization RolesDave Getty
If your Company wants to treat Data as an Asset, it needs a Chief Data Officer to initiate significant changes in the Roles and Responsibilities of the Data Governance, IT Data Management and Business Analyst Data Scientist organizations. This presentation describes how the resulting organizations might look and behave.
This document discusses how to create a data governance dashboard by connecting it to Trillium Software's data quality platform. It recommends including business rule metadata, the rules library, decision points, and time series analysis in the dashboard. It demonstrates how to use the OLE DB provider to abstract the platform's architecture and define tables to retrieve metrics, rules results, metadata, and more. Connecting the dashboard to the repository in this way allows efficient ongoing monitoring of data quality.
The document discusses three case studies of companies that faced challenges managing reference data from multiple sources:
1) A mutual fund company had issues tracking identifiers like CUSIPs as funds changed names through mergers and acquisitions.
2) A student lending institution struggled to quickly create new loan products due to manual spreadsheet processes.
3) The same student lender faced problems reconciling inconsistent account data from seven different loan servicers in different formats.
Data Verification and Validation - Melissa Data helps you in analyzing, cleansing & match data quality, data standardization and data quality management services for your organization.
This document discusses an agile solution for enterprise data modeling and data management provided by A.I. Consultancy Limited and Pacific Rim Telecomm Datacomm Ltd. It outlines the benefits of enterprise data modeling, problems with traditional top-down approaches, and their hybrid agile solution using off-the-shelf modeling tools. Their solution aims to deliver initial data models quickly and support ongoing data governance through modular implementation and tailored training.
Emagia Master Class 3 | Integrated Order-to-Cash (OTC) Transformation for Glo...emagia
Integrated Order-to-Cash (OTC) Transformation for Global Shared Service Organizations. Emagia Master Class 3. Automated consolidated receivables – in total and by customer from multiple ERP’s
https://www.emagia.com/master-class/
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
The Importance of Master Data ManagementDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to:
Structure their Data Management processes around these principles
Incorporate Data Quality engineering into the planning of reference and MDM
Understand why MDM is so critical to their organization’s overall data strategy
Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Chief Data Officer (CDO) Organization RolesDave Getty
If your Company wants to treat Data as an Asset, it needs a Chief Data Officer to initiate significant changes in the Roles and Responsibilities of the Data Governance, IT Data Management and Business Analyst Data Scientist organizations. This presentation describes how the resulting organizations might look and behave.
This document discusses how to create a data governance dashboard by connecting it to Trillium Software's data quality platform. It recommends including business rule metadata, the rules library, decision points, and time series analysis in the dashboard. It demonstrates how to use the OLE DB provider to abstract the platform's architecture and define tables to retrieve metrics, rules results, metadata, and more. Connecting the dashboard to the repository in this way allows efficient ongoing monitoring of data quality.
The document discusses three case studies of companies that faced challenges managing reference data from multiple sources:
1) A mutual fund company had issues tracking identifiers like CUSIPs as funds changed names through mergers and acquisitions.
2) A student lending institution struggled to quickly create new loan products due to manual spreadsheet processes.
3) The same student lender faced problems reconciling inconsistent account data from seven different loan servicers in different formats.
Data Verification and Validation - Melissa Data helps you in analyzing, cleansing & match data quality, data standardization and data quality management services for your organization.
This document discusses an agile solution for enterprise data modeling and data management provided by A.I. Consultancy Limited and Pacific Rim Telecomm Datacomm Ltd. It outlines the benefits of enterprise data modeling, problems with traditional top-down approaches, and their hybrid agile solution using off-the-shelf modeling tools. Their solution aims to deliver initial data models quickly and support ongoing data governance through modular implementation and tailored training.
Emagia Master Class 3 | Integrated Order-to-Cash (OTC) Transformation for Glo...emagia
Integrated Order-to-Cash (OTC) Transformation for Global Shared Service Organizations. Emagia Master Class 3. Automated consolidated receivables – in total and by customer from multiple ERP’s
https://www.emagia.com/master-class/
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
The Importance of Master Data ManagementDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to:
Structure their Data Management processes around these principles
Incorporate Data Quality engineering into the planning of reference and MDM
Understand why MDM is so critical to their organization’s overall data strategy
Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Data Quality Management: Cleaner Data, Better Reportingaccenture
This document discusses Accenture's regulatory reporting framework and offerings around data quality management. It provides an overview of Accenture's high-performance financial reporting framework, which aims to consolidate frameworks, processes, and technology to create efficiencies across reporting functions. It also summarizes Accenture's regulatory reporting offerings, including data quality management, capability design, target operating models, and regulatory reporting vendor implementation support. Finally, it covers key aspects of data quality management, such as issue classification, management processes, governance structures, root cause analysis, and issue prioritization. The goal is to help financial institutions improve data quality, reporting accuracy and efficiency.
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...DATAVERSITY
Operational Data Governance is more than a stewardship process for critical Business Assets. As organizations build structure around KPI’s and other critical data, a workflow develops that revolves around the sources and supply chain for that critical data. There can be many aspects to changes and inconsistencies affecting the final results of the supply chain. Inaccurate usage of data can result in audit penalties as well as erroneous report summaries and conclusions.
Is it coming from the correct authoritative source? Has the data been profiled? Has it met it’s threshold?
Gaps in the supply chain from incorrect pathways may lead dead ends or lost sources.
The value of understanding the entire supply chain cannot be overstated. When changes occur at and point, end users can validate that correct business standards, rules and policies have been applied to the critical data within the supply chain. Your organization can rest easy that you are not at risk for exposure due to improper usage, security, and compliance.
Join this webinar to uncover how companies are using data lineage to accomplish data supply chain transparency. You’ll also see the direct value clear data lineage can give to your business and IT landscape today.
The Data Governance Annual Conference and International Data Quality Conference in San Diego was very good. I recommend this conference for business and IT persons responsible for data quality and data governenance. There will be a similar event in Orlando, December 2010. This is the presentation I delivered to a grateful audience.
China data-mngnt-solution-market-reportssuser7709011
The document provides an overview of the China data management solutions market. It defines data management solutions as systems that effectively collect, store, analyze and apply massive amounts of data to extract valuable information and support enterprise decisions. Typical applications include data warehouses for structured data and analytics, and data lakes for storage of large volumes of raw data. The market is expected to continue expanding due to policies supporting data use and more data application scenarios. Key trends include increased cloud deployment, and integration of data lakes and warehouses.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
Analytics Organization Modeling for Maturity Assessment and Strategy DevelopmentVijay Raj
The paper discusses Business Intelligence Organization Modeling as a concept along with practical implementation aspects with reference to Analytics and Business Intelligence Strategy in large enterprises. BI organization modeling revolves around the ability to model the patterns of BI prevalent within a corporate structure to assess organizational capability and maturity, and there by contributing towards BI strategy development and implementation. The paper also details Analytics & BI organization modeling in a predominantly SAP based enterprise ecosystem and is demonstrated with BI systems based on the SAP NetWeaver Business Warehouse (BW) using data discovery and machine learning techniques. The data discovery process for Analytics & BI organization modeling is carried out using SAP Lumira Data Visualization tool connected to an SAP NetWeaver BW based Global Enterprise Data Warehousing and Reporting System.
Eclipse day Sydney 2014 BIG data presentationSai Paravastu
Big data refers to large, complex datasets that are difficult to process using traditional database management tools. This document discusses big data challenges, growth drivers, opportunities, and new approaches to processing and analytics using tools like Hadoop, MongoDB, and BIRT. It provides an overview of how BIRT supports connecting to and visualizing data from different sources, including Hive, Cassandra, and MongoDB, and how the BIRT community contributes to its open source development.
Unleash Your Data While Ensuring Governance and Security: Reporting, Prism, a...Workday, Inc.
For IT leaders, unlocking data is foundational to organizational success in a digital-first world. But what can you do to deliver data and insight to reduce the digital acceleration gap within your organization?
View this slide deck to learn:
How to unlock data for faster insights
How Workday Prism Analytics gives you the analytics you need in one secure place
How Workday strengthens partnerships with HR and finance
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
The document summarizes key topics from the book "Data Governance for the Executive" by Jim Orr. It discusses how data governance has traditionally been viewed narrowly but should be seen as information asset management that drives business performance. The document also outlines how data governance can demonstrate value to executives by reducing costs, improving revenues, and mitigating risks across industries. Companies estimate losing millions annually due to data quality issues.
The document discusses how big data analytics can drive business transformations. It describes key business trends like socialization, collaboration and gamification that are shaping businesses. Examples are provided of how companies like Goldcorp used crowdsourcing of data to transform their business. The presentation emphasizes that companies that can efficiently harvest and analyze large amounts of data will have a competitive advantage in changing market dynamics.
Master Data Management - Gartner Presentation303Computing
This document discusses Digital Realty's implementation of a master data management (MDM) system. It provides an overview of MDM and why most projects fail. Digital Realty is succeeding by taking an agile approach with flexible multi-domain solutions. They leverage data virtualization and have identified data champions to manage master data domains like customers, products, facilities and people. The MDM implementation has provided benefits like improved data quality monitoring, faster integration of acquired companies, and ensuring compliance with data governance policies. Digital Realty is working to expand their MDM to additional transactional and dimensional master data entities.
3 Keys To Successful Master Data Management - Final PresentationJames Chi
This document discusses keys to successful master data management including process, governance, and architecture. It summarizes a survey finding that while many companies see data as an asset, only around 20% have implemented master data management. Successful MDM requires alignment with business objectives, clear governance models, and comprehensive solution architectures. The document advocates establishing policies, procedures, standards, governance, and tools to create and maintain high-quality shared reference data.
- The document discusses data management strategies for accountants and compliance with accounting standards. It addresses data quality, governance, and assurance frameworks.
- Various definitions are provided around data quality, governance, and frameworks to structure quality activities and assess data quality.
- A data governance strategy is recommended that sets core data standards, focuses initially on critical data, and uses a slow-burn approach of monthly/quarterly reviews and a program of works to gradually improve data quality and maturity.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
The Data Management challenges each organization faces are unique in their priority and severity. Therefore the structure and composition of a Data Organization is one of the major success factors for establishing a successful and sustainable data program. In this presentation, we will review the developmental stages of a data organization, the models and the choices for establishing the right structure to the organization in addition to the process for selecting the team members that will produce high-performance business results.
MDM & RDM: Enabling a One Company Supply Chain in a Decentralized EnvironmentOrchestra Networks
Presented @ MDM/DG Summit NYC 2015 (Oct 6, 2015)
In this presentation Lydia Tilsley (UTC Operations) and Larry Keyser (UTCHQ IT) from the United Technologies Corporation (UTC) describe how reference and master data management is being used to support UTC's "One Supply Chain" initiatives at UTC.
This document discusses master data management (MDM) and presents a new approach using an operational data hub with streamlined MDM. It begins by defining MDM and noting the complexity of traditional MDM systems. Traditional MDM uses relational databases and lengthy processes for data modeling, ETL, and integration across siloed systems. This leads to systems that are slow, expensive, and brittle. The document then introduces an alternative approach of using an operational data hub to directly integrate transactional applications and handle various data types. It describes how streamlined MDM can load data as-is, match and merge data at the point of engagement, maintain metadata and provenance for all data, and provide a simplified and flexible architecture
A term paper for a strategy class at the Asian Institute of Management. It talks about the competitive advantages of Facebook and how presents an industry model for the social media space.
(if you use this ppt - please give credit. thank you)
There are 7 main types of documentaries: docusoaps, reality TV, fly on the wall, mixed, self reflective, docudrama, and fully narrated. Docusoaps follow individuals or groups over a long period in an observational style. Reality TV shows real life drama for entertainment and information. Fly on the wall documentaries film subjects unaware with narration linking the story. Mixed documentaries use interviews, footage, and narration. Self reflective documentaries follow people who acknowledge the camera. Docudramas reconstruct past events. Fully narrated documentaries have narration throughout to explain the visuals.
Data Quality Management: Cleaner Data, Better Reportingaccenture
This document discusses Accenture's regulatory reporting framework and offerings around data quality management. It provides an overview of Accenture's high-performance financial reporting framework, which aims to consolidate frameworks, processes, and technology to create efficiencies across reporting functions. It also summarizes Accenture's regulatory reporting offerings, including data quality management, capability design, target operating models, and regulatory reporting vendor implementation support. Finally, it covers key aspects of data quality management, such as issue classification, management processes, governance structures, root cause analysis, and issue prioritization. The goal is to help financial institutions improve data quality, reporting accuracy and efficiency.
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...DATAVERSITY
Operational Data Governance is more than a stewardship process for critical Business Assets. As organizations build structure around KPI’s and other critical data, a workflow develops that revolves around the sources and supply chain for that critical data. There can be many aspects to changes and inconsistencies affecting the final results of the supply chain. Inaccurate usage of data can result in audit penalties as well as erroneous report summaries and conclusions.
Is it coming from the correct authoritative source? Has the data been profiled? Has it met it’s threshold?
Gaps in the supply chain from incorrect pathways may lead dead ends or lost sources.
The value of understanding the entire supply chain cannot be overstated. When changes occur at and point, end users can validate that correct business standards, rules and policies have been applied to the critical data within the supply chain. Your organization can rest easy that you are not at risk for exposure due to improper usage, security, and compliance.
Join this webinar to uncover how companies are using data lineage to accomplish data supply chain transparency. You’ll also see the direct value clear data lineage can give to your business and IT landscape today.
The Data Governance Annual Conference and International Data Quality Conference in San Diego was very good. I recommend this conference for business and IT persons responsible for data quality and data governenance. There will be a similar event in Orlando, December 2010. This is the presentation I delivered to a grateful audience.
China data-mngnt-solution-market-reportssuser7709011
The document provides an overview of the China data management solutions market. It defines data management solutions as systems that effectively collect, store, analyze and apply massive amounts of data to extract valuable information and support enterprise decisions. Typical applications include data warehouses for structured data and analytics, and data lakes for storage of large volumes of raw data. The market is expected to continue expanding due to policies supporting data use and more data application scenarios. Key trends include increased cloud deployment, and integration of data lakes and warehouses.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
Analytics Organization Modeling for Maturity Assessment and Strategy DevelopmentVijay Raj
The paper discusses Business Intelligence Organization Modeling as a concept along with practical implementation aspects with reference to Analytics and Business Intelligence Strategy in large enterprises. BI organization modeling revolves around the ability to model the patterns of BI prevalent within a corporate structure to assess organizational capability and maturity, and there by contributing towards BI strategy development and implementation. The paper also details Analytics & BI organization modeling in a predominantly SAP based enterprise ecosystem and is demonstrated with BI systems based on the SAP NetWeaver Business Warehouse (BW) using data discovery and machine learning techniques. The data discovery process for Analytics & BI organization modeling is carried out using SAP Lumira Data Visualization tool connected to an SAP NetWeaver BW based Global Enterprise Data Warehousing and Reporting System.
Eclipse day Sydney 2014 BIG data presentationSai Paravastu
Big data refers to large, complex datasets that are difficult to process using traditional database management tools. This document discusses big data challenges, growth drivers, opportunities, and new approaches to processing and analytics using tools like Hadoop, MongoDB, and BIRT. It provides an overview of how BIRT supports connecting to and visualizing data from different sources, including Hive, Cassandra, and MongoDB, and how the BIRT community contributes to its open source development.
Unleash Your Data While Ensuring Governance and Security: Reporting, Prism, a...Workday, Inc.
For IT leaders, unlocking data is foundational to organizational success in a digital-first world. But what can you do to deliver data and insight to reduce the digital acceleration gap within your organization?
View this slide deck to learn:
How to unlock data for faster insights
How Workday Prism Analytics gives you the analytics you need in one secure place
How Workday strengthens partnerships with HR and finance
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
The document summarizes key topics from the book "Data Governance for the Executive" by Jim Orr. It discusses how data governance has traditionally been viewed narrowly but should be seen as information asset management that drives business performance. The document also outlines how data governance can demonstrate value to executives by reducing costs, improving revenues, and mitigating risks across industries. Companies estimate losing millions annually due to data quality issues.
The document discusses how big data analytics can drive business transformations. It describes key business trends like socialization, collaboration and gamification that are shaping businesses. Examples are provided of how companies like Goldcorp used crowdsourcing of data to transform their business. The presentation emphasizes that companies that can efficiently harvest and analyze large amounts of data will have a competitive advantage in changing market dynamics.
Master Data Management - Gartner Presentation303Computing
This document discusses Digital Realty's implementation of a master data management (MDM) system. It provides an overview of MDM and why most projects fail. Digital Realty is succeeding by taking an agile approach with flexible multi-domain solutions. They leverage data virtualization and have identified data champions to manage master data domains like customers, products, facilities and people. The MDM implementation has provided benefits like improved data quality monitoring, faster integration of acquired companies, and ensuring compliance with data governance policies. Digital Realty is working to expand their MDM to additional transactional and dimensional master data entities.
3 Keys To Successful Master Data Management - Final PresentationJames Chi
This document discusses keys to successful master data management including process, governance, and architecture. It summarizes a survey finding that while many companies see data as an asset, only around 20% have implemented master data management. Successful MDM requires alignment with business objectives, clear governance models, and comprehensive solution architectures. The document advocates establishing policies, procedures, standards, governance, and tools to create and maintain high-quality shared reference data.
- The document discusses data management strategies for accountants and compliance with accounting standards. It addresses data quality, governance, and assurance frameworks.
- Various definitions are provided around data quality, governance, and frameworks to structure quality activities and assess data quality.
- A data governance strategy is recommended that sets core data standards, focuses initially on critical data, and uses a slow-burn approach of monthly/quarterly reviews and a program of works to gradually improve data quality and maturity.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
The Data Management challenges each organization faces are unique in their priority and severity. Therefore the structure and composition of a Data Organization is one of the major success factors for establishing a successful and sustainable data program. In this presentation, we will review the developmental stages of a data organization, the models and the choices for establishing the right structure to the organization in addition to the process for selecting the team members that will produce high-performance business results.
MDM & RDM: Enabling a One Company Supply Chain in a Decentralized EnvironmentOrchestra Networks
Presented @ MDM/DG Summit NYC 2015 (Oct 6, 2015)
In this presentation Lydia Tilsley (UTC Operations) and Larry Keyser (UTCHQ IT) from the United Technologies Corporation (UTC) describe how reference and master data management is being used to support UTC's "One Supply Chain" initiatives at UTC.
This document discusses master data management (MDM) and presents a new approach using an operational data hub with streamlined MDM. It begins by defining MDM and noting the complexity of traditional MDM systems. Traditional MDM uses relational databases and lengthy processes for data modeling, ETL, and integration across siloed systems. This leads to systems that are slow, expensive, and brittle. The document then introduces an alternative approach of using an operational data hub to directly integrate transactional applications and handle various data types. It describes how streamlined MDM can load data as-is, match and merge data at the point of engagement, maintain metadata and provenance for all data, and provide a simplified and flexible architecture
A term paper for a strategy class at the Asian Institute of Management. It talks about the competitive advantages of Facebook and how presents an industry model for the social media space.
(if you use this ppt - please give credit. thank you)
There are 7 main types of documentaries: docusoaps, reality TV, fly on the wall, mixed, self reflective, docudrama, and fully narrated. Docusoaps follow individuals or groups over a long period in an observational style. Reality TV shows real life drama for entertainment and information. Fly on the wall documentaries film subjects unaware with narration linking the story. Mixed documentaries use interviews, footage, and narration. Self reflective documentaries follow people who acknowledge the camera. Docudramas reconstruct past events. Fully narrated documentaries have narration throughout to explain the visuals.
Suchi Watagodakumbura has over 15 years of experience working with children and youth with special needs. She has a diploma in Special Education and certificates in Applied Behavior Analysis and Autism Spectrum Disorders. Suchi has worked in various roles including as a Behavior Interventionist, Special Education Assistant, Respite Worker, and Learning Support Tutor. She has experience implementing ABA programs and supporting students in school settings. Suchi is highly committed to helping students achieve educational and life skills goals.
The document is a curriculum vitae for Ilham Fauzi, an Indonesian man with experience working in offshore oil fields as a medic, radio operator, and ambulance nurse. It includes his personal details, skills, job experience from 2015-2008 working in offshore oil operations in the Persian Gulf, education history, medical certifications and training, and descriptions of his responsibilities and duties in various roles providing emergency medical services and communications offshore and as an ambulance nurse.
El documento proporciona 10 claves para que los estudiantes sean exitosos en entornos de aprendizaje virtual. Estas incluyen desarrollar hábitos de concentración en lugar de atención dispersa, ser proactivo en lugar de reactivo, manejar bien las fechas límite, incluir actividades de presentación para generar confianza, y establecer comunicación cercana con los estudiantes.
Selsun Blue is an over-the-counter dandruff shampoo containing selenium sulfide as the active ingredient. Selenium sulfide is an antifungal agent that is effective in treating dandruff, seborrheic dermatitis, tinea versicolor, and tinea capitis. Its mechanism of action involves inhibiting fungal growth and slowing the proliferation of skin cells. Selsun Blue should be applied to the scalp or affected areas of the skin and left on for several minutes before rinsing for proper treatment of various fungal infections. While generally safe as directed, in large amounts selenium sulfide can potentially cause toxicity in humans.
El documento lista las principales líneas de productos y servicios de America Group SRL. Incluye productos como servidores, almacenamiento, switches, impresoras, software de virtualización y licenciamiento. También detalla los servicios de pre-venta, implementación, soporte técnico, garantías y diseño/dimensionamiento que ofrece la compañía.
Este documento describe un proyecto de 9 sesiones sobre hábitos de vida saludables para estudiantes de 14-15 años. El proyecto incluye encuestas sobre hábitos de vida, análisis de resultados, investigación sobre la ingesta calórica recomendada y elaboración de un menú saludable de 5 días. Los estudiantes trabajarán en grupos para completar las actividades y compartirán sus hallazgos con otro grupo a través de TwinSpace.
SIS-G provides business intelligence, data warehousing, and information integration solutions to help clients make better, more timely decisions. They extract key data from corporate systems and deliver virtual data-driven applications. SIS-G utilizes an agile methodology and offers strategic planning, project delivery, and infrastructure optimization services including data governance, roadmapping, requirements gathering, design, development, and testing. Their solutions are customized to each client's specific needs.
Enterprise Excellence Systems is a Puerto Rico-based consulting firm that provides various business services including business process management, strategic planning and implementation, operational excellence, project management, product and process engineering, quality management systems, and business application development. The document outlines the company's vision, mission, values, offerings, and scope. It also provides examples of previous client engagements and success stories.
GeodataIT provides data solutions and services to help organizations solve data challenges, streamline operations, and realize returns on their investments. They focus on commercial open-source technologies and expanding services to help businesses where data presents difficulties. GeodataIT delivers customized solutions including assessments, development, testing, and ongoing support to address clients' data problems and improve their bottom lines.
This document is a curriculum vitae for Anuj Gupta that outlines his professional experience and technical skills. It summarizes that he has over 7 years of experience as an IT consultant providing strategic guidance to clients. He has worked as a team leader and senior engineer on various projects for companies like Newgen Software, Infosys, RBS Services, and Airtel. His technical skills include languages like Java, XML, and SQL as well as frameworks like Hibernate, RESTful web services, and Hadoop. He also has experience in data analytics using tools like R, machine learning algorithms, and natural language processing.
This document provides a summary of Mohammed Kaleem's professional experience and qualifications. He has over 25 years of experience in business intelligence, with expertise in MicroStrategy, Informatica, and data warehousing. Some of his roles include senior consultant, solution architect, and lead developer. He has extensive experience designing, developing, and implementing BI solutions for many large companies.
The document describes BluePrint v.Smart Parking, an intelligent automated parking solution that optimizes site management through visibility of demand, availability, and usage data gathered from an AI-powered system. It discusses how the solution streamlines day-to-day car park logistics and ensures expectations are not only met but exceeded. The solution is provided by ANS and their engagement model aims to successfully deliver business objectives through an agile approach from inception to ongoing operations.
Have you begun to see the value of Enterprise Data Management? If so, perhaps you’ve decided that simply buying more hardware is no longer a viable option for your IT department. Despite the ever-falling cost of hardware, each new machine you add will increase your labor, power, and cooling costs over time.
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1. DATA WAREHOUSE, BUSINESS INTELLIGENCE
& INFORMATION INTEGRATION SOLUTIONS
SISG Services - Overview.doc 1
Strategic
Information
Systems
Group
701 Carlyle Court
Northbrook, IL
60062
888.372.1815
www.sisg.com
While market, competitive, regulatory and technological change accelerates, management’s
pursuit of profitability remains constant. In an increasingly project driven economy where
business models continually evolve, it is critical that you agilely align projects with business
strategy and complete them on time and within budget. In this information driven world, SIS-
G can provide you with Business Intelligence solutions that provide you access to more
relevant, timely, and accurate information, which will give you the competitive edge that
separates you from competitors.
SIS-G brings the business and technical expertise required to extract key business data from
diverse corporate systems and deliver data driven solutions today. We can provide all this
through our own virtual environments, where we create business intelligence applications with
your data, without taxing your systems or budget.
SIS-G utilizes an agile project methodology to iteratively deliver data solutions, contribute deep
domain expertise in Data Management and enhance your in-house development capability with
the flexibility of high tech experts on demand. Our full project life cycle skill sets can take your
data initiative from conceptualization to implementation.
SIS-G SERVICE OFFERINGS
SIS-G has a long, strong history building Business Intelligence, Data Warehousing, Data
Integration and Data Conversion solutions that consistently deliver high value to blue chip
clients. We appropriately blend IT Data services to deliver any complete information solution,
for example real-time, cloud, embedded analytics, event driven decision-making agents and
predictive models, needed as your business continues to require more frequent, diverse insight
from larger volumes of data. Below is a summarized description of services we offer to clients,
but we work with you to create custom solutions to target and satisfy your specific business
needs.
Strategic Solution Planning Services:
SIS-G offers the following services that define and plan project work required to deliver the
data related dependencies supporting your Corporate Strategic Plan implementation.
Information Management Roadmap – Depict an efficient, business oriented
conceptual approach for how investments in Data Assets will be allocated to corporate
information initiatives over time, to increase Information Asset value and deliver Business
Intelligence that enables decisions that accomplish strategic goals.
Enterprise Data Governance – Coordinate cross functional stakeholders to institute an
organized governing body, policies, procedures and stewards, chartered with responsibility
to provide clean, auditable, transparent data, for data related initiatives.
Agile Project Management – Direct iterative project activities with Project Management
Institute practices and assume responsibility for time, quality and budget.
Strategic Metric Design – Collaborate with corporate Strategic Planners and Industry
Experts to negotiate the critical, quantifiable metrics to be used by management to run the
business and evaluate company performance.
Data Warehouse Assessment – Review of all existing data integration and data
warehouse application requirements, metrics, models, designs, code, performance, test
2. DATA WAREHOUSE, BUSINESS INTELLIGENCE
& INFORMATION INTEGRATION SOLUTIONS
SISG Services - Overview.doc 2
Strategic
Information
Systems
Group
701 Carlyle Court
Northbrook, IL
60062
888.372.1815
www.sisg.com
plans, controls, project methodology, templates and procedures, highlighting gaps, issues
and opportunities for modernization, while associating costs of application ownership with
derived benefits.
Data Quality Audit – Evaluate relevant source system data, for accuracy, reasonableness
and consistency, highlighting quality issues, cleansing needs and data transformation
requirements. Review Master Data Management identity processes and results.
Project Delivery Services:
SIS-G offers the following comprehensive services comprising all phases of the system
development lifecycle to implement a complete solution.
Collaborative Requirements Gathering – Facilitate Joint Requirements Planning
sessions with collaborative workflow and requirements capture tools, to efficiently prioritize
business requirements captured from many users in many formats at many times, and
refine them into proposed solution release bundles.
Data Profiling – Review of source system data element distinct values, relationships with
each other, definitions and other detailed metadata, required as input for Data
Architecture, Transformation Design and Project Estimation.
Data Architecture – Model the logical and physical data structures, their relationships
and metadata. Forward engineer the target state model in all database environments.
Project Estimation – Calculate expected project costs from design through
implementation using prior project experience and refined formulas based on the number
and nature of data source, transformation and delivery objects designed per approved
requirements.
Collaborative Application Design – Specify source to target data mappings, process
flow and data transformation logic traceable to requirements, using design templates
which are importable to the development ETL toolset generating initial mapping code.
Collaborative Application Development – Code and Unit Test using visual software
development tools, reusable components and collaborative workflow for extract,
transformation, load and delivery of information, per the Collaborative Application Design.
Automated Testing – Automate test case data creation and test script execution using
testing tools with traceability to required use cases. Leverage SIS-G’s Advanced Test
Automation Solution (ATAS) add-on software to inventory and re-use test scripts for each
iterative release. Promote test scripts to an automated regression-testing environment to
be run repetitively prior to each subsequent release, to reduce test cost, increase software
quality and eliminate undesired production impacts.
Infrastructure Optimization Services:
SIS-G consultants stay abreast of the latest trends in Information Management technology
through regular training, certifications and participation in vendor partnership programs which
include cloud hosted environments for software installs, training and integration proof of
concepts. This adds value to client implementations while delivering the following technical
services to optimize infrastructures.
3. DATA WAREHOUSE, BUSINESS INTELLIGENCE
& INFORMATION INTEGRATION SOLUTIONS
SISG Services - Overview.doc 3
Strategic
Information
Systems
Group
701 Carlyle Court
Northbrook, IL
60062
888.372.1815
www.sisg.com
Technical Architecture Blueprints – Graphically depict the current and future
development, test and production technical architecture, for use in communicating the
current infrastructure and planning the migration to the future state.
Proof of Technology – Evaluate whether specific source system data can be processed
with proposed technology versions and the extent that multi-vendor software installations
can be integrated to satisfy predefined business requirements, prior to investing in either
technology or projects to build comprehensive development, test and production solutions.
Cloud Computing – Configure elastic, reliable virtualized software and hardware
resources provided as a service over the Internet, to agilely enable project Proof of
Technology, development, test or production that is on demand, scalable and pay-as-you-
go, without dependence on your company’s IT infrastructure.
Center of Excellence Implementation – Establish a centralized in-house Business
Intelligence and Information Integration technology organization to coalesce knowledge,
establish best practices, define standards, enforce standards, maintain infrastructure and
educate IT Staff and Business Users in the technology.
Software Upgrades – Analyze, plan, and safely upgrade your development, test and
production software installations to the latest versions and train your Center of Excellence,
IT project staff and users in the new features and functionality of the release.
Technology Training – Formally educate users and IT staff in software tools, modeling
techniques and project delivery methods used throughout the project lifecycle.
Performance Tuning – Analyze, design, code, test and implement technical (SQL, code,
database, ETL, server, grid, network, etc.) modifications that improve system performance
without changing the functionality of the applications.
Grid Computing – install and configure software to divide and apportion segments of a
software program among several computers acting in concert to complete the task faster.
High Availability Software – install and configure software that ensures the availability
of system resources for data warehouse or data integration users, in the wake of
component failures in the system.
Vendor Selection –Evaluate hardware and software tools and vendors independently in
the Information Management space, including solutions for Requirements Capture, ETL,
Automated Testing, Massive Parallel Processing (MPP) appliances, Unstructured Database
and Analytics.
WHY CHOOSE SIS-G?
By allowing us to help you define data management strategies, champion new fact driven
business processes and implement best practices, your company will be enabled to make
better-informed decisions, improve operational efficiencies and create new revenue channels.
Clients should consider partnering with SIS-G for the following reasons:
Exclusive focus on Data Warehouse, Business Intelligence and Information Integration
has enabled SISG to accumulate the critical mass of project experience, technical
skills, partnerships, best practices and methodologies to excel within that niche.
4. DATA WAREHOUSE, BUSINESS INTELLIGENCE
& INFORMATION INTEGRATION SOLUTIONS
SISG Services - Overview.doc 4
Strategic
Information
Systems
Group
701 Carlyle Court
Northbrook, IL
60062
888.372.1815
www.sisg.com
We have made a significant investment in learning highly productive software tools, for
requirements capture, data modeling, ETL, BI, project workflow collaboration and
automated testing, to reduce overall project cost, inject value in solutions for your
problems and reduce risk in tool implementation and adoption.
SIS-G’s Virtual and Cloud development environments for Technology Training and
Proof of Technology reduce your project start-up timelines, cost and risk.
Business backgrounds (MBA/CPA) of SIS-G consultants skilled with collaborative
capture tools and facilitated methods, reduce project risk and defects.
We exclusively hire experienced consultants and then train them in our best practices,
methodologies and productivity software.
While focused on technical or business specialties, the scope of each consultant’s
expertise covers the full project life cycle with broad and deep knowledge in our niche.
Our core competencies in Data Modeling and ETL (Extract, Transformation and Load)
are more valuable than the marketing and presentation core competencies of our
competitors, since our focus areas contain the largest opportunities for value creation.
SIS-G is right-sized for your business needs. You are an important client to us and
have immediate access to our Executives, so all your requests are promptly and
efficiently addressed.
Vendor partnerships provide SIS-G consultants familiar and immediate access to cloud
software, training and support resources, reducing technical issue resolution time.
Our specialized business model, management experience, technical knowledge, vendor
partnerships, virtual development capabilities and education, enable us to deliver insightful
strategic counsel and high value implementation services with cost effective national coverage.
We are a highly competitive alternative to general purpose staffing firms and marketing based
consulting firms that sell inexperience at high prices.
OUR TEAM
Strategic Information Systems Group (SIS-G) is a boutique IT consulting team of experienced
consultants specializing in Business Intelligence and Information Integration projects since
1994. Established in 1989 by former executives of General Electric Capital, we have provided
many Fortune 1000 companies with solutions that have made significant, positive, impacts in
their organizations. SIS-G consultants hold advanced business degrees and certifications
(MBA/CPA/PMP) in addition to technical degrees and certifications, providing the blend of
business and technology experience needed to analyze, design and build high performance
strategic information driven applications. We are successful because we work with you to
leverage what you have, build what you need, increase the value of your data assets and leave
your organization stronger than when we started.
For more information please contact:
Dave Getty, Principal Partner
Direct Line: 847-452-6053
Email: dgetty@sisg.com