Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing:
• Knowing what data is available to support programs and other business functions
• Data is more difficult to access
• Without insight into the lineage of data, it is risky to use as the basis for critical decisions
• Analyzing data and extracting insights to influence outcomes is difficult at best
The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives.
Learn how to kick start your data governance intiatives and how an enterprise data management platform can help you:
• Innovate and expose hidden opportunities
• Break down data access barriers and ensure data is trusted
• Provide actionable information at the speed of business
Although Big Data is changing enterprise data architecture models, support for Big Data extends beyond the walls of IT. The most successful companies are focused on building strong business cases for Big Data to drive support, adoption and funding though the enterprise.
This webinar investigated the two perspectives in constructing a business case for Big Data as well as how to create a compelling business case for Big Data success.
During this webinar, we covered:
-Challenges Creating Business Cases for Big Data
-Two perspectives for building Big Data business-cases
-Building the business-focused case and getting to monetized benefits
-Fortifying your business case with IT-benefits
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.
Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing:
• Knowing what data is available to support programs and other business functions
• Data is more difficult to access
• Without insight into the lineage of data, it is risky to use as the basis for critical decisions
• Analyzing data and extracting insights to influence outcomes is difficult at best
The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives.
Learn how to kick start your data governance intiatives and how an enterprise data management platform can help you:
• Innovate and expose hidden opportunities
• Break down data access barriers and ensure data is trusted
• Provide actionable information at the speed of business
Although Big Data is changing enterprise data architecture models, support for Big Data extends beyond the walls of IT. The most successful companies are focused on building strong business cases for Big Data to drive support, adoption and funding though the enterprise.
This webinar investigated the two perspectives in constructing a business case for Big Data as well as how to create a compelling business case for Big Data success.
During this webinar, we covered:
-Challenges Creating Business Cases for Big Data
-Two perspectives for building Big Data business-cases
-Building the business-focused case and getting to monetized benefits
-Fortifying your business case with IT-benefits
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.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Data Quality Management: Cleaner Data, Better Reportingaccenture
In this new Accenture Finance & Risk presentation we explore a process to investigate, prioritize and resolve data quality issues, key to creating a more efficient and accurate reporting environment. View our presentation to learn more.
For more on regulatory reporting, see presentation on Financial Reporting Robotics: http://bit.ly/2qaLK9y
Visit our blog for latest Regulatory Insights: https://accntu.re/2qnXs1B
Revolution In Data Governance - Transforming the customer experiencePaul Dyksterhouse
The foundation of managing data security and big data is implementing data governance. Data Owners, Metadata tagging, Customer feedback and Continuous Improvement are critical facets to provide the transparency and consistency so that customer's can trust the data, and make informed decisions.
Data Privatisation, Data Anonymisation, Data Pseudonymisation and Differentia...Alan McSweeney
Your data has value to your organisation and to relevant data sharing partners. It has been expensively obtained. It represents a valuable asset on which a return must be generated. To achieve the value inherent in the data you need to be able to make it appropriately available to others, both within and outside the organisation.
Organisations are frequently data rich and information poor, lacking the skills, experience and resources to convert raw data into value.
These notes outline technology approaches to achieving compliance with data privacy regulations and legislation while providing access to data.
There are different routes to making data accessible and shareable within and outside the organisation without compromising compliance with data protection legislation and regulations and removing the risk associated with allowing access to personal data:
• Differential Privacy – source data is summarised and individual personal references are removed. The one-to-one correspondence between original and transformed data has been removed
• Anonymisation – identifying data is destroyed and cannot be recovered so individual cannot be identified. There is still a one-to-one correspondence between original and transformed data
• Pseudonymisation – identifying data is encrypted and recovery data/token is stored securely elsewhere. There is still a one-to-one correspondence between original and transformed data
These technologies and approaches are not mutually exclusive – each is appropriate to differing data sharing and data access use cases
The data privacy regulatory and legislative landscape is complex and getting even more complex so an approach to data access and sharing that embeds compliance as a matter of course is required.
Appropriate technology appropriately implemented and operated is a means of managing and reducing risks of re-identification by making the time, skills, resources and money necessary to achieve this unrealistic.
Technology is part of a risk management approach to data privacy. There is wider operational data sharing and data privacy framework that includes technology aspects, among other key areas. Using these technologies will embed such compliance by design into your data sharing and access facilities. This will allow you to realise value from your data successfully.
Poor data quality should be a primary driver in selecting and implementing a Master Data Management solution, and yet 64% of organizations say it's the reason they abandoned the evaluation.*
*Profisee Topline Market Study 2020
Data Governance That Drives the Bottom LinePrecisely
The financial services sector is investing heavily in data governance solutions to find, understand and trust customer data, while also managing compliance risk around an ever-evolving regulatory landscape more effectively.
But do you still find it difficult to get management support for data governance budgets? Do you have the tools you need to determine the “business cost of data” accurately? Can you show the CFO an ROI projection he can count on? Are you able to answer, “Will I see results on the top line or the bottom line?” Are your business line leaders able to identify areas that are losing money due to data problems?
If you answered no to any of these questions, join Precisely in our upcoming webinar that will focus on how Financial Services companies can monetize the return on investment for data governance and how to relate it to business results that every senior leader understands.
Join this on-demand webinar to learn about:
- How to select data initiatives based on corporate goals and strategy
- How to connect the dots from data challenges (quality, availability, accuracy, currency) to specific business metrics around
- How to quantify the data contribution to improving business performance around
- How to leverage metadata and linage to get a 360-degree understanding of your data
- How to evaluate data assets by assigning measures and defining scores.
- How to assign accountability to assets and processes
- How to define and execute the workflows needed to implement corrective actions
- How to highlight the benefits of data governance
The Centre Cannot Hold: Making IT Architecture Relevant In A Post IT WorldAlan McSweeney
Business has a consistently poor experience of the internal IT function. It is now all too easy for the business to bypass the central IT function. There is a business shift to cloud service providers offering infrastructure-less solutions with no perceived IT involvement. Outsourcing and the divestment of IT functions in response to business wishes to remove the overhead. The business need to respond to the interrelated developments of digital, mobile and social computing and perceived inability of the central IT function to respond.
If the IT function cannot react to the requirements of the business due to business pressures, the business will go elsewhere. Shadow IT - the acquisition of IT solutions outside the control of the IT function - is an unpleasant and common reality. 50% of IT expenditure is routinely spent outside the control of the IT function. Shadow IT is a symptom of a post-IT world.
The central IT function loses relevance and control. Businesses reduce their reliance on the core IT function.
IT architecture should act as a glue joining the business strategy to the IT strategy. IT architecture needs to operate as an internal business consulting And advisory function. An effective business oriented IT architecture function can get the correct balance between too little and too much, too slowly and too quickly. The IT Architecture team needs to operate as a team rather than a set of siloed internally focussed IT roles, involving business as well as technologists.
Data and the enterprise mission: putting data at the corecorfinancial
Data matters to Financial Services firms. It is their stock-in-trade, a strategic asset that without an accurate and timely data set they cannot operate effectively, they cannot price risk fully and their capital allocation calls are unlikely to be optimal. Data is the ultimate collateral of these firms. For many, it requires a transformational change in their systems, technology and processes How then do you embed strategic data into your enterprise architecture?
Read 2 minute guide
Achieving Digital Transformation in RegulatoryCary Smithson
Significant change is underway in Regulatory Affairs as life science companies re-evaluate their global operating capabilities in light of today's data-driven standards and newly available technologies. Mounting pressure to operate more efficiently worldwide is driving companies to optimize and harmonize processes, improve data usage and management, and adopt shared global systems. In this presentation, Cary Smithson will discuss potential ways to leverage the latest technologies to address today's business challenges in Regulatory and provide a practical approach for driving transformation and enabling greater efficiency.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
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.
Improve IT Security and Compliance with Mainframe Data in SplunkPrecisely
Avoid security blind spots with an enterprise-wide view.
If your organization relies on Splunk as its security nerve center, you can’t afford to leave out your mainframes.
They work with the rest of your IT infrastructure to support critical business applications–and they need to be
viewed in that wider context to address potential security blind spots.
Although the importance of including mainframe data in Splunk is undeniable, many organizations have left it out
because Splunk doesn’t natively support IBM Z® environments. Learn how Precisely Ironstream can help with a
straight-forward, powerful approach for integrating your mainframe security data into Splunk, and making it actionable
once it’s there.
Enterprise Data World Webinars: Master Data Management: Ensuring Value is Del...DATAVERSITY
Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities
A Logical Architecture is Always a Flexible Architecture (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3joZa0a
The current data landscape is fragmented, not just in location but also in terms of processing paradigms: data lakes, IoT architectures, NoSQL, and graph data stores, SaaS applications, etc. are found coexisting with relational databases to fuel the needs of modern analytics, ML, and AI. The physical consolidation of enterprise data into a central repository, although possible, is both expensive and time-consuming. A logical data warehouse is a modern data architecture that allows organizations to leverage all of their data irrespective of where the data is stored, what format it is stored in, and what technologies or protocols are used to store and access the data.
Watch this session to understand:
- What is a logical data warehouse and how to architect one
- The benefits of logical data warehouse – speed with agility
- Customer use case depicting logical architecture implementation
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Data Quality Management: Cleaner Data, Better Reportingaccenture
In this new Accenture Finance & Risk presentation we explore a process to investigate, prioritize and resolve data quality issues, key to creating a more efficient and accurate reporting environment. View our presentation to learn more.
For more on regulatory reporting, see presentation on Financial Reporting Robotics: http://bit.ly/2qaLK9y
Visit our blog for latest Regulatory Insights: https://accntu.re/2qnXs1B
Revolution In Data Governance - Transforming the customer experiencePaul Dyksterhouse
The foundation of managing data security and big data is implementing data governance. Data Owners, Metadata tagging, Customer feedback and Continuous Improvement are critical facets to provide the transparency and consistency so that customer's can trust the data, and make informed decisions.
Data Privatisation, Data Anonymisation, Data Pseudonymisation and Differentia...Alan McSweeney
Your data has value to your organisation and to relevant data sharing partners. It has been expensively obtained. It represents a valuable asset on which a return must be generated. To achieve the value inherent in the data you need to be able to make it appropriately available to others, both within and outside the organisation.
Organisations are frequently data rich and information poor, lacking the skills, experience and resources to convert raw data into value.
These notes outline technology approaches to achieving compliance with data privacy regulations and legislation while providing access to data.
There are different routes to making data accessible and shareable within and outside the organisation without compromising compliance with data protection legislation and regulations and removing the risk associated with allowing access to personal data:
• Differential Privacy – source data is summarised and individual personal references are removed. The one-to-one correspondence between original and transformed data has been removed
• Anonymisation – identifying data is destroyed and cannot be recovered so individual cannot be identified. There is still a one-to-one correspondence between original and transformed data
• Pseudonymisation – identifying data is encrypted and recovery data/token is stored securely elsewhere. There is still a one-to-one correspondence between original and transformed data
These technologies and approaches are not mutually exclusive – each is appropriate to differing data sharing and data access use cases
The data privacy regulatory and legislative landscape is complex and getting even more complex so an approach to data access and sharing that embeds compliance as a matter of course is required.
Appropriate technology appropriately implemented and operated is a means of managing and reducing risks of re-identification by making the time, skills, resources and money necessary to achieve this unrealistic.
Technology is part of a risk management approach to data privacy. There is wider operational data sharing and data privacy framework that includes technology aspects, among other key areas. Using these technologies will embed such compliance by design into your data sharing and access facilities. This will allow you to realise value from your data successfully.
Poor data quality should be a primary driver in selecting and implementing a Master Data Management solution, and yet 64% of organizations say it's the reason they abandoned the evaluation.*
*Profisee Topline Market Study 2020
Data Governance That Drives the Bottom LinePrecisely
The financial services sector is investing heavily in data governance solutions to find, understand and trust customer data, while also managing compliance risk around an ever-evolving regulatory landscape more effectively.
But do you still find it difficult to get management support for data governance budgets? Do you have the tools you need to determine the “business cost of data” accurately? Can you show the CFO an ROI projection he can count on? Are you able to answer, “Will I see results on the top line or the bottom line?” Are your business line leaders able to identify areas that are losing money due to data problems?
If you answered no to any of these questions, join Precisely in our upcoming webinar that will focus on how Financial Services companies can monetize the return on investment for data governance and how to relate it to business results that every senior leader understands.
Join this on-demand webinar to learn about:
- How to select data initiatives based on corporate goals and strategy
- How to connect the dots from data challenges (quality, availability, accuracy, currency) to specific business metrics around
- How to quantify the data contribution to improving business performance around
- How to leverage metadata and linage to get a 360-degree understanding of your data
- How to evaluate data assets by assigning measures and defining scores.
- How to assign accountability to assets and processes
- How to define and execute the workflows needed to implement corrective actions
- How to highlight the benefits of data governance
The Centre Cannot Hold: Making IT Architecture Relevant In A Post IT WorldAlan McSweeney
Business has a consistently poor experience of the internal IT function. It is now all too easy for the business to bypass the central IT function. There is a business shift to cloud service providers offering infrastructure-less solutions with no perceived IT involvement. Outsourcing and the divestment of IT functions in response to business wishes to remove the overhead. The business need to respond to the interrelated developments of digital, mobile and social computing and perceived inability of the central IT function to respond.
If the IT function cannot react to the requirements of the business due to business pressures, the business will go elsewhere. Shadow IT - the acquisition of IT solutions outside the control of the IT function - is an unpleasant and common reality. 50% of IT expenditure is routinely spent outside the control of the IT function. Shadow IT is a symptom of a post-IT world.
The central IT function loses relevance and control. Businesses reduce their reliance on the core IT function.
IT architecture should act as a glue joining the business strategy to the IT strategy. IT architecture needs to operate as an internal business consulting And advisory function. An effective business oriented IT architecture function can get the correct balance between too little and too much, too slowly and too quickly. The IT Architecture team needs to operate as a team rather than a set of siloed internally focussed IT roles, involving business as well as technologists.
Data and the enterprise mission: putting data at the corecorfinancial
Data matters to Financial Services firms. It is their stock-in-trade, a strategic asset that without an accurate and timely data set they cannot operate effectively, they cannot price risk fully and their capital allocation calls are unlikely to be optimal. Data is the ultimate collateral of these firms. For many, it requires a transformational change in their systems, technology and processes How then do you embed strategic data into your enterprise architecture?
Read 2 minute guide
Achieving Digital Transformation in RegulatoryCary Smithson
Significant change is underway in Regulatory Affairs as life science companies re-evaluate their global operating capabilities in light of today's data-driven standards and newly available technologies. Mounting pressure to operate more efficiently worldwide is driving companies to optimize and harmonize processes, improve data usage and management, and adopt shared global systems. In this presentation, Cary Smithson will discuss potential ways to leverage the latest technologies to address today's business challenges in Regulatory and provide a practical approach for driving transformation and enabling greater efficiency.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
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.
Improve IT Security and Compliance with Mainframe Data in SplunkPrecisely
Avoid security blind spots with an enterprise-wide view.
If your organization relies on Splunk as its security nerve center, you can’t afford to leave out your mainframes.
They work with the rest of your IT infrastructure to support critical business applications–and they need to be
viewed in that wider context to address potential security blind spots.
Although the importance of including mainframe data in Splunk is undeniable, many organizations have left it out
because Splunk doesn’t natively support IBM Z® environments. Learn how Precisely Ironstream can help with a
straight-forward, powerful approach for integrating your mainframe security data into Splunk, and making it actionable
once it’s there.
Enterprise Data World Webinars: Master Data Management: Ensuring Value is Del...DATAVERSITY
Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities
A Logical Architecture is Always a Flexible Architecture (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3joZa0a
The current data landscape is fragmented, not just in location but also in terms of processing paradigms: data lakes, IoT architectures, NoSQL, and graph data stores, SaaS applications, etc. are found coexisting with relational databases to fuel the needs of modern analytics, ML, and AI. The physical consolidation of enterprise data into a central repository, although possible, is both expensive and time-consuming. A logical data warehouse is a modern data architecture that allows organizations to leverage all of their data irrespective of where the data is stored, what format it is stored in, and what technologies or protocols are used to store and access the data.
Watch this session to understand:
- What is a logical data warehouse and how to architect one
- The benefits of logical data warehouse – speed with agility
- Customer use case depicting logical architecture implementation
Innovation Without Compromise: The Challenges of Securing Big DataCloudera, Inc.
Hadoop is a powerful tool for today’s enterprise – providing unified storage of all data and metadata, regardless of format or source, and multiple frameworks for robust processing and analytics. However, this flexibility and scale also presents challenges for securing and governing this data.
Join IDC analysts, Carl Olofson and Mike Versace, as they discuss the changing world of big data security with Eddie Garcia, Information Security Architect at Cloudera, and Anil Earla, Chief Data and Analytics Officer of IS at Visa.
During this live roundtable discussion, you will:
Gain an understanding of how securing big data differs from traditional enterprise security
Learn about the latest tools and initiatives around Hadoop platform security
Hear how one of the largest payment processors approaches big data security and regulatory concerns
Introductory session on Cloud Computing Technology and Current market offerings from various vendors.
Evolving of Cloud base platform, Need of Cloud and Benefits with its some limitations and current challenges.
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization Denodo
Watch here: https://bit.ly/2NGQD7R
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But that scenario is rapidly changing with the increasing adoption of real-time data virtualization - a paradigm shift in the approach that organizations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes centre stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission-critical.
Attend this session to learn:
- Learn how you can meet cloud and data science challenges with data virtualization.
- Why data virtualization is increasingly finding enterprise-wide adoption
- Discover how customers are reducing costs and improving ROI with data virtualization
Watch full webinar here: https://bit.ly/2vN59VK
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
- What data virtualization really is.
- How it differs from other enterprise data integration technologies.
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations.
Watch full webinar here: https://bit.ly/2Y0vudM
What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad of consumers.
Register to attend this session to learn:
- What is Data Virtualization?
- Why do I need Data Virtualization in my organization?
- How do I implement Data Virtualization in my enterprise?
GDPR Noncompliance: Avoid the Risk with Data VirtualizationDenodo
You can watch the full webinar on-demand here: https://goo.gl/2f2RYF
In its recent report “Predictions 2018: A year of reckoning”, Forrester predicts that 80% of firms affected by GDPR will not comply with the regulation by May 2018. Of those noncompliant firms, 50% will intentionally not comply.
Compliance doesn’t have to be this difficult! What if you have an opportunity to facilitate GDPR compliance with a mature technology and significant cost reduction? Data virtualization is a mature, cost-effective technology that enables privacy by design to facilitate GDPR compliance.
Attend this session to learn:
• How data virtualization provides a GDPR compliance foundation with data catalog, auditing, and data security.
• How you can enable single enterprise-wide data access layer with guardrails.
• Why data virtualization is a must-have capability for compliance use cases.
• How Denodo’s customers have facilitated compliance.
IT 833 INFORMATION GOVERNANCEDr. Isaac T. GbenleChaptemariuse18nolet
IT 833 INFORMATION GOVERNANCE
Dr. Isaac T. Gbenle
Chapter 15 – Information Governance for Cloud Computing
*
*
[email protected] Asante, 2019
[email protected] Asante, 2019
CHAPTER GOALSBe able to define cloud computingWhat are the key characteristics of cloud computing?What are the four cloud deployment models?Describe common security threats with cloud computingContrast the concerns of cloud computing with the benefitsExplain the guidelines for managing documents and records using cloud computingExplain IG guidelines for cloud computing
*
WHY IS CLOUD COMPUTING SUCH A “BIG DEAL”?
*
Changes our entire way of thinking about computing and IT
Provides scalable, adjustable resources
Cost savings to business
Combines newest architectures, system software, hardware speeds, and lower storage costs
Instant resources at the disposal of business
Frees up the IT Department to focus on business functional unit needs
Concerns for privacy and security are overlooked
What is Cloud Computing?
“Cloud Computing is a shared resource that provides dynamic access to computing services that may range from raw computing power to basic infrastructure to fully operational and supported applications”
Smallwood, Information Governance: Concepts, Strategies and Best Practices, page 286
*
What is Cloud Computing?
“A model for enabling convenient on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction”Peter Mell and Tim Grance, “NIST Definition of Cloud Computing, Version 15, 10-07-09, www.nist.gov
“Shared resource that proavides dynamic access to computing services that may range from raw computing power, to basic infrastructure, to fully operational and supported applications”. –from your textbook page 286
*
*
[email protected] Asante, 2019
[email protected] Asante, 2019
CHARACTERISTICS OF CLOUD COMPUTINGOn-Demand Self-ServiceBroad network accessResource pooling Rapid ElasticityMeasured Service
*
Misconceptions of Cloud ComputingCloud Computing is a service-oriented architectureMisconception: Cloud Computing does not “move the organization to the cloud”Misconception: If you don’t migrate to a cloud solution you are protected from the dangers of cloud computing
*
CLOUD DEPLOYMENT MODELSPrivate Cloud –Dedicated to and operated by a single enterpriseCommunity Cloud – Where Cloud infrastructure is shared by several organizationsPublic Cloud – Cloud infrastructure is made available to the general public or industrial groupHybrid Cloud – Combined approach – composition of two or more clouds
*
THREATS OF CLOUD COMPUTING
Information Loss
Fix: Agreement by provider to follow standard operating procedure for data backup, archival and retention
Data Loss Insurance
Information Breaches
Fix: DLS Implementation
Strong Encryption
Secure Storage, management and doc destruction procedures
Contractual Agreements
Insurance C ...
IT 833 INFORMATION GOVERNANCEDr. Isaac T. GbenleChapte.docxvrickens
IT 833 INFORMATION GOVERNANCE
Dr. Isaac T. Gbenle
Chapter 15 – Information Governance for Cloud Computing
*
*
[email protected] Asante, 2019
[email protected] Asante, 2019
CHAPTER GOALSBe able to define cloud computingWhat are the key characteristics of cloud computing?What are the four cloud deployment models?Describe common security threats with cloud computingContrast the concerns of cloud computing with the benefitsExplain the guidelines for managing documents and records using cloud computingExplain IG guidelines for cloud computing
*
WHY IS CLOUD COMPUTING SUCH A “BIG DEAL”?
*
Changes our entire way of thinking about computing and IT
Provides scalable, adjustable resources
Cost savings to business
Combines newest architectures, system software, hardware speeds, and lower storage costs
Instant resources at the disposal of business
Frees up the IT Department to focus on business functional unit needs
Concerns for privacy and security are overlooked
What is Cloud Computing?
“Cloud Computing is a shared resource that provides dynamic access to computing services that may range from raw computing power to basic infrastructure to fully operational and supported applications”
Smallwood, Information Governance: Concepts, Strategies and Best Practices, page 286
*
What is Cloud Computing?
“A model for enabling convenient on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction”Peter Mell and Tim Grance, “NIST Definition of Cloud Computing, Version 15, 10-07-09, www.nist.gov
“Shared resource that proavides dynamic access to computing services that may range from raw computing power, to basic infrastructure, to fully operational and supported applications”. –from your textbook page 286
*
*
[email protected] Asante, 2019
[email protected] Asante, 2019
CHARACTERISTICS OF CLOUD COMPUTINGOn-Demand Self-ServiceBroad network accessResource pooling Rapid ElasticityMeasured Service
*
Misconceptions of Cloud ComputingCloud Computing is a service-oriented architectureMisconception: Cloud Computing does not “move the organization to the cloud”Misconception: If you don’t migrate to a cloud solution you are protected from the dangers of cloud computing
*
CLOUD DEPLOYMENT MODELSPrivate Cloud –Dedicated to and operated by a single enterpriseCommunity Cloud – Where Cloud infrastructure is shared by several organizationsPublic Cloud – Cloud infrastructure is made available to the general public or industrial groupHybrid Cloud – Combined approach – composition of two or more clouds
*
THREATS OF CLOUD COMPUTING
Information Loss
Fix: Agreement by provider to follow standard operating procedure for data backup, archival and retention
Data Loss Insurance
Information Breaches
Fix: DLS Implementation
Strong Encryption
Secure Storage, management and doc destruction procedures
Contractual Agreements
Insurance C ...
Modern Data Integration Expert Session Webinar ibi
William McKnight, President of McKnight Consulting Group and Information Builders’ Jake Freivald discuss the tools needed for a successful modern data integration.
Information Builders provides the industry’s most scalable software solutions for data management and analytics. We help organizations operationalize and monetize their data through insights that drive action. Our integrated platform for BI, analytics, data integration, and data quality, combined with our proven expertise, delivers value faster, with less risk. We believe data and analytics are the drivers of digital transformation, and we’re on a mission to help our customers capitalize on new opportunities in the connected world. Information Builders is headquartered in New York, NY, with global offices, and remains one of the largest privately held companies in the industry.
Best Practices in the Cloud for Data Management (US)Denodo
Watch here: https://bit.ly/2Npt82U
If you have data, you are engaged in data management—be sure to do it effectively.
As organizations are assessing how COVID-19 has impacted their operations, new possibilities and uncharted routes are becoming the norm for many businesses. While exploring and implementing different deployment and operational models, the question of data management naturally surfaces while considering how these changes impact your data. Is this the right time to focus on data management? The reality is that if you have data, you are engaged in data management and so the real question is, are you doing it well?
Join Brice Giesbrecht from Caserta and Mitesh Shah from Denodo to explore data management challenges and solutions facing data driven organizations.
Watch full webinar here: https://buff.ly/2mHGaLA
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
• What data virtualization really is
• How it differs from other enterprise data integration technologies
• Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
Fast Data Strategy Houston Roadshow PresentationDenodo
Fast Data Strategy Houston Roadshow focused on the next industrial revolution on the horizon, driven by the application of big data, IoT and Cloud technologies.
• Denodo’s innovative customer, Anadarko, elaborated on how data virtualization serves as the key component in their prescriptive and predictive analytics initiatives, driven by multi-structured data ranging from customer data to equipment data.
• Denodo’s session, Unleashing the Power of Data, described the complexity of the modern data ecosystem and how to overcome challenges and successfully harness insights.
• Our Partner Noah Consulting, an expert analytics solutions provider in the energy industry, explained how your peers are innovating using new business models and reducing cost in areas such as Asset Management and Operations by leveraging Data Virtualization and Prescriptive and Predictive Analytics.
For more information on upcoming roadshows near you, follow this link: https://goo.gl/WBDHiE
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