Business and IT are facing the challenge of getting real and urgent value from ever-expanding information sources. Building independent silos of big data analytics is no longer enough. True progress comes only by integrating data from traditional operational and informational sources with the new sources that are becoming available, whether from social media or interconnected machines.
In this April 2014 BrightTALK webinar, Dr. Barry Devlin describes the thinking, architecture, tools and methods needed to achieve a new joined-up, comprehensive data environment.
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
Paper which discusses the notion that Data is NOT the "new Oil". We hear copious amounts said that Data is an asset, it's got to be managed, few people in the business understand it & so on. The phrase "Data is the new Oil" gets used many times, yet is rarely (if ever) justified. This paper is aimed to raise the level of debate from a subliminal nod to a conscious examination of the characteristics of different "assets" (particularly Oil) and to compare them with those of the 'Data asset".
Written by Christopher Bradley, CDMP Fellow, VP Professional Development DAMA International & 38 years Information Management experience, much of it in the Oil & Gas industry.
This takes a look at the architectural constructs that are used for building business intelligence systems and how they are used in business processes to improve marketing, better serve customers, and maximize organizational efficiency.
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
Paper which discusses the notion that Data is NOT the "new Oil". We hear copious amounts said that Data is an asset, it's got to be managed, few people in the business understand it & so on. The phrase "Data is the new Oil" gets used many times, yet is rarely (if ever) justified. This paper is aimed to raise the level of debate from a subliminal nod to a conscious examination of the characteristics of different "assets" (particularly Oil) and to compare them with those of the 'Data asset".
Written by Christopher Bradley, CDMP Fellow, VP Professional Development DAMA International & 38 years Information Management experience, much of it in the Oil & Gas industry.
This takes a look at the architectural constructs that are used for building business intelligence systems and how they are used in business processes to improve marketing, better serve customers, and maximize organizational efficiency.
Big Data 101 - Creating Real Value from the Data Lifecycle - Happiest Mindshappiestmindstech
The big impact of Big Data in the post-modern world is
unquestionable, un-ignorable and unstoppable today.
While there are certain discussions around Big Data being
really big, here to stay or just an over hyped fad; there are
facts as shared in the following sections of this whitepaper
that validate one thing - there is no knowing of the limits
and dimensions that data in the digital world can assume.
A Data Management Advisors discussion paper comparing the characteristics of different types of "assets" and asking the question "Is the data asset REALLY different"?
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Dana Gardner
Transcript of a discussion on how HTI Labs in London provides the means and governance with their Schematiq tool to bring critical data to the interface that users want most.
"Enterprise Architecture and the Information Age Enterprise" @ CSDM2010 Leon Kappelman
Talk I gave in Paris on 28-Oct-10 @ the Complex System Design and Management Conference on "Enterprise Architecture and the Information Age Enterprise." Excellent event, wonderful people, beautiful city.
Successfully Kickstarting Data Governance's Social Dynamics: Define, Collabor...Stijn (Stan) Christiaens
Learn how to launch your data governance program, by answering three questions:
- What does my data mean: collect and manage business definitions and relations, taxonomies and classifications, business rules and ontologies;
- How can I involve all stakeholders: engage them across business units and geographies, with stewards, data owners, … in a guiding workflow;
- How do I operationalize data governance: link MDM, DQ and BI to the business, use business-driven semantic modelling, achieve end-to end traceabilitiy. During this session we will use examples from different verticals: Finance, Government, Utilities,… .
We discuss their main drivers for starting a Data Governance initiative, as well as their pragmatic approach in moving from gradual roll out to support and sustain their Data Governance program.
Data-Ed: Show Me the Money: The Business Value of Data and ROIData Blueprint
This webinar originally aired on Tuesday, December 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Failure to successfully monetize data management investments sets up an unfortunate loop of fixing symptoms without addressing the underlying problems. As organizations begin to understand poor data management practices as the root causes of many of their problems, they become more willing to make the required investments in our profession. This presentation uses specific examples to illustrate the costs of poor data management. Join us and learn how you can apply similar tactics at your organization to justify funding and gain management approval.
Investing in AI: Moving Along the Digital Maturity CurveCognizant
Digitally mature businesses are more likely to consider themselves at an advanced stage of AI adoption, according to our recent study, enabling them to turn data into insights at the scale and precision required today.
Prof. Gregoris Mentzas, Director, Information Management Unit
(National Technical University of Athens) presented "Towards Proactive Enterprise Intelligence" (FInES Workshop at Aalborg)
Business unIntelligence - a Whistle Stop TourBarry Devlin
The old world of business intelligence is being transformed into a new biz-tech ecosystem. Analytics is forcing the recombination of operational and informational systems in a consistent and coherent IT environment for all business activities. Big data—despite the hype—introduces two very different types of information that transform how business processes interact with the external world. Together, these directions are driving a new BI, so different to its prior form that I call it “Business unIntelligence”. This session covers:
- Business drivers and results of the biz-tech ecosystem
- Modern conceptual and logical architectures for information, process and people
- Positioning of all forms of business analytic and big data
A sample of my book "Business unIntelligence - Insight and Innovation beyond Analytics and Big Data", published by Technics Publications, 2013.
Chapter 5 shows the evolution of the Data Warehouse architecture and provides a description of some aspects of a modern Information architecture.
The book can be ordered in hard and softcopy formats at http://bit.ly/BunI-TP1
Lewis Crawford's presentation from the BI Boss event in Leeds, focussing on our perspective on Big Data, Big Data projects, what to avoid, and how to make it work for you.
Big Data 101 - Creating Real Value from the Data Lifecycle - Happiest Mindshappiestmindstech
The big impact of Big Data in the post-modern world is
unquestionable, un-ignorable and unstoppable today.
While there are certain discussions around Big Data being
really big, here to stay or just an over hyped fad; there are
facts as shared in the following sections of this whitepaper
that validate one thing - there is no knowing of the limits
and dimensions that data in the digital world can assume.
A Data Management Advisors discussion paper comparing the characteristics of different types of "assets" and asking the question "Is the data asset REALLY different"?
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Dana Gardner
Transcript of a discussion on how HTI Labs in London provides the means and governance with their Schematiq tool to bring critical data to the interface that users want most.
"Enterprise Architecture and the Information Age Enterprise" @ CSDM2010 Leon Kappelman
Talk I gave in Paris on 28-Oct-10 @ the Complex System Design and Management Conference on "Enterprise Architecture and the Information Age Enterprise." Excellent event, wonderful people, beautiful city.
Successfully Kickstarting Data Governance's Social Dynamics: Define, Collabor...Stijn (Stan) Christiaens
Learn how to launch your data governance program, by answering three questions:
- What does my data mean: collect and manage business definitions and relations, taxonomies and classifications, business rules and ontologies;
- How can I involve all stakeholders: engage them across business units and geographies, with stewards, data owners, … in a guiding workflow;
- How do I operationalize data governance: link MDM, DQ and BI to the business, use business-driven semantic modelling, achieve end-to end traceabilitiy. During this session we will use examples from different verticals: Finance, Government, Utilities,… .
We discuss their main drivers for starting a Data Governance initiative, as well as their pragmatic approach in moving from gradual roll out to support and sustain their Data Governance program.
Data-Ed: Show Me the Money: The Business Value of Data and ROIData Blueprint
This webinar originally aired on Tuesday, December 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Failure to successfully monetize data management investments sets up an unfortunate loop of fixing symptoms without addressing the underlying problems. As organizations begin to understand poor data management practices as the root causes of many of their problems, they become more willing to make the required investments in our profession. This presentation uses specific examples to illustrate the costs of poor data management. Join us and learn how you can apply similar tactics at your organization to justify funding and gain management approval.
Investing in AI: Moving Along the Digital Maturity CurveCognizant
Digitally mature businesses are more likely to consider themselves at an advanced stage of AI adoption, according to our recent study, enabling them to turn data into insights at the scale and precision required today.
Prof. Gregoris Mentzas, Director, Information Management Unit
(National Technical University of Athens) presented "Towards Proactive Enterprise Intelligence" (FInES Workshop at Aalborg)
Business unIntelligence - a Whistle Stop TourBarry Devlin
The old world of business intelligence is being transformed into a new biz-tech ecosystem. Analytics is forcing the recombination of operational and informational systems in a consistent and coherent IT environment for all business activities. Big data—despite the hype—introduces two very different types of information that transform how business processes interact with the external world. Together, these directions are driving a new BI, so different to its prior form that I call it “Business unIntelligence”. This session covers:
- Business drivers and results of the biz-tech ecosystem
- Modern conceptual and logical architectures for information, process and people
- Positioning of all forms of business analytic and big data
A sample of my book "Business unIntelligence - Insight and Innovation beyond Analytics and Big Data", published by Technics Publications, 2013.
Chapter 5 shows the evolution of the Data Warehouse architecture and provides a description of some aspects of a modern Information architecture.
The book can be ordered in hard and softcopy formats at http://bit.ly/BunI-TP1
Lewis Crawford's presentation from the BI Boss event in Leeds, focussing on our perspective on Big Data, Big Data projects, what to avoid, and how to make it work for you.
Three signs your architecture is too small for big data. Camp IT December 2014Craig Jordan
Three capability gaps that a traditional business intelligence architecture has with respect to processing big data and recommended extensions to address them.
Data Virtualization – Gateway to a Digital Business - Barry DevlinDenodo
Next-Generation Data Management Afternoon
with InfoRoad and Denodo. Presentation by Dr Barry Devlin, Founder and Principal 9sight Consulting on data virtualization.
This webinar featuring Claudia Imhoff, President of Intelligent Solutions & Founder of the Boulder BI Brain Trust (BBBT), Matt Schumpert, Director of Product Management and Azita Martin, CMO at Datameer, will highlight the latest technology trends in extending BI with big data analytics and the top high impact use cases.
Attendees will hear about:
-- The extended architecture for today's modern analytics environment
-- The Internet of Things (IoT) and big data
-- The evolution of analytics – from descriptive to prescriptive
-- High impact use cases as a result of the changing analytics world
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
2015 is knocking on the door and will be an exciting and surprising year for the BI industry. However, not everything will be a surprise for Panorama as we are always on top of the latest trends influencing the Business Intelligence community.
• What will the future hold for the industry?
• What are our BI experts thoughts, predictions and internal assessments on what new directions the Business Intelligence community will see in the coming year?
• Countdown of the most important trends in the industry
Digital revolution is disrupting businesses like never before! Ability to extract actionable insight from a large amount of disparate data has become the determining factor of competitive advantage! Everyday new business models are created around data and forcing the incumbents to reinvent themselves to be relevant. Consumer facing businesses felt this pressure early on but eventually every business need to be data driven. But what is the best strategy to address this digital disruption? Our experience says the core data infrastructure modernization is the logical starting point! In this session, we will share trends, strategies and our experience on rejuvenating data integration landscape to address digital disruptions.
The customer journey could essentially be divided into 7 elements. We’ll touch upon the issue of ‘Privacy’ and how one balance social and commercial value. Practical examples of
customer analytics at its best will be discussed as well as the importance of the eco-system.
Smarter Analytics: Supporting the Enterprise with AutomationInside Analysis
The Briefing Room with Barry Devlin and WhereScape
Live Webcast on June 10, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=5230c31ab287778c73b56002bc2c51a
The data warehouse is intended to support analysis by making the right data available to the right people in a timely fashion. But conditions change all the time, and when data doesn’t keep up with the business, analysts quickly turn to workarounds. This leads to ungoverned and largely un-managed side projects, which trade short-term wins for long-term trouble. One way to keep everyone happy is by creating an integrated environment that pulls data from all sources, and is capable of automating both the model development and delivery of analyst-ready data.
Register for this episode of The Briefing Room to hear data warehousing pioneer and Analyst Barry Devlin as he explains the critical components of a successful data warehouse environment, and how traditional approaches must be augmented to keep up with the times. He’ll be briefed by WhereScape CEO Michael Whitehead, who will showcase his company’s data warehousing automation solutions. He’ll discuss how a fast, well-managed and automated infrastructure is the key to empowering faster, smarter, repeatable decision making.
Visit InsideAnlaysis.com for more information.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Arne Rossmann outlines why the Business Data Lake works and which Services the Business Data Lake should provide. Organizations can use the Business Data Lake concept best when they standardize, industrialize and innovate.
Presented by Arne Rossman, Capgemini Germany, at the OOP Conference, 31 January 2017
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/