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DMBoK Discipline: Document Management

Chris Bradley continues to explain the different Information Management disciplines in the DAMA DMBoK 'wheel' - this time focusing on “Document Management”
Recorded Mar 15 2016 48 mins
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Chris Bradley
Presentation preview: DMBoK Discipline: Document Management

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  • Unsupervised learning to uncover advanced cyber attacks Aug 22 2017 10:00 am UTC 45 mins
    Rafael San Miguel Carrasco, Senior Specialist, British Telecom EMEA
    This case study is framed in a multinational company with 300k+ employees, present in 100+ countries, that is adding one extra layer of security based on big data analytics capabilities, in order to provide net-new value to their ongoing SOC-related investments.

    Having billions of events being generated on a weekly basis, real-time monitoring must be complemented with deep analysis to hunt targeted and advanced attacks.

    By leveraging a cloud-based Spark cluster, ElasticSearch, R, Scala and PowerBI, a security analytics platform based on anomaly detection is being progressively implemented.

    Anomalies are spotted by applying well-known analytics techniques, from data transformation and mining to clustering, graph analysis, topic modeling, classification and dimensionality reduction.
  • Tensorflow: Architecture and use case Apr 11 2017 8:00 am UTC 45 mins
    Gema Parreño Piqueras. AI product developer
    The webinar drives into the introduction of the architecture of Tensorflow and the designing of use case.

    You will learn:
    -What is an artificial neuron?
    -What is Tensorflow? What are its advantages? What's it used for?
    -Designing graphs in Tensorflow
    -Tips & tricks for designing neural nets
    -Use case
  • Long-term Data Retention: Challenges, Standards and Best Practices Feb 16 2017 6:00 pm UTC 75 mins
    Simona Rabinovici-Cohen, IBM, Phillip Viana, IBM, Sam Fineberg
    The demand for digital data preservation has increased drastically in recent years. Maintaining a large amount of data for long periods of time (months, years, decades, or even forever) becomes even more important given government regulations such as HIPAA, Sarbanes-Oxley, OSHA, and many others that define specific preservation periods for critical records.

    While the move from paper to digital information over the past decades has greatly improved information access, it complicates information preservation. This is due to many factors including digital format changes, media obsolescence, media failure, and loss of contextual metadata. The Self-contained Information Retention Format (SIRF) was created by SNIA to facilitate long-term data storage and preservation. SIRF can be used with disk, tape, and cloud based storage containers, and is extensible to any new storage technologies. It provides an effective and efficient way to preserve and secure digital information for many decades, even with the ever-changing technology landscape.
Join this webcast to learn:
    •Key challenges of long-term data retention
    •How the SIRF format works and its key elements
    •How SIRF supports different storage containers - disks, tapes, CDMI and the cloud
    •Availability of Open SIRF

    SNIA experts that developed the SIRF standard will be on hand to answer your questions.
  • Comparison of ETL v Streaming Ingestion,Data Wrangling in Machine/Deep Learning Feb 15 2017 11:00 am UTC 45 mins
    Kai Waehner, Technology Evangelist, TIBCO
    A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 50% of the whole project.

    This session compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming analytics ingestion, and data wrangling within visual analytics. Various options and their trade-offs are shown in live demos using different advanced analytics technologies and open source frameworks such as R, Python, Apache Spark, Talend or KNIME. The session also discusses how this is related to visual analytics, and best practices for how the data scientist and business user should work together to build good analytic models.

    Key takeaways for the audience:
    - Learn various option for preparing data sets to build analytic models
    - Understand the pros and cons and the targeted persona for each option
    - See different technologies and open source frameworks for data preparation
    - Understand the relation to visual analytics and streaming analytics, and how these concepts are actually leveraged to build the analytic model after data preparation
  • Data Science Apps: Beyond Notebooks with Apache Toree, Spark and Jupyter Gateway Feb 14 2017 1:00 pm UTC 60 mins
    Natalino Busa, Head of Applied Data Science, Teradata
    Jupyter notebooks are transforming the way we look at computing, coding and problem solving. But is this the only “data scientist experience” that this technology can provide?

    In this webinar, Natalino will sketch how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis. In the background, these apps are still powered by well understood and documented Jupyter notebooks.

    They will present an architecture which is composed of four parts: a jupyter server-only gateway, a Scala/Spark Jupyter kernel, a Spark cluster and a angular/bootstrap web application.
  • Visualization: A tool for knowledge Feb 14 2017 11:00 am UTC 45 mins
    Luis Melgar, Visual Reporter at Univision News
    During the last decades, concepts such as Big Data and Data Visualization have become more popular and present in our daily lives. But what is visualization?

    Visualization is an intellectual discipline that allows to generate knowledge through visual forms. And as in every other field, there are good and bad practices that can help consumers or mislead them.

    In this webinar, we will address:

    -What it’s Data Visualization and why it’s important
    -How to choose the right graphic forms in order to represent complex information
    -Interactivity and new narratives
    -What tools can be used
  • How to Setup and Manage a Corporate Self Service Analytics Environment Feb 14 2017 9:00 am UTC 45 mins
    Ronald van Loon, Director Business Development (Adversitement) and Ian Macdonald, Principal Technologist (Pyramid Analytics)
    As companies face the challenges arising from a surge in the number of customer interactions and data, it can be difficult to successfully manage the vast quantities of information and still provide a positive customer experience. It is incumbent upon businesses to create a consumer-centric experience that is powered by (predictive) analytics.

    Adopting a data-driven approach through a corporate self-service analytics (SSA) environment is integral to strengthening your data and analytics strategy.


    During the webinar, speakers Ronald van Loon & Ian Macdonald will:

    •Expand upon on the benefits of a corporate SSA environment
    •Define how your business can successfully manage a corporate SSA environment
    •Present supportive case studies
    •Demonstrate practical examples of analytic governance in an SSA environment using BI Office from Pyramid Analytics.
    •Discuss practical tips on how to get started
    •Cover how to avoid common pitfalls associated with a SSA environment

    Stay tuned for a Q&A with speaker Ronald van Loon and domain expert Ian Macdonald, Principal Technologist, Pyramid Analytics.
  • AI in Finance: AI in regulatory compliance, risk management, and auditing Recorded: Jan 18 2017 49 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    AI to Improve Regulatory Compliance, Governance & Auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests.

    Learn:
    Machine learning and cognitive computing for:
    -Regulatory Compliance
    -Process and Financial Audit
    -Data Management

    Recommendations:
    -Data computing systems
    -Tools and skills
  • The Art of Storage Management Recorded: Dec 15 2016 62 mins
    George Crump, Curtis Preston
    Any organization that takes a moment to study the data on their primary storage system will quickly realize that the majority (as much as 90 percent) of data that is stored on it has not been accessed for months if not years. Moving this data to a secondary tier of storage could free up massive amount of capacity, eliminating a storage upgrade for years. Making this analysis frequently is called data management, and proper management of data can not only reduce costs it can improve data protection, retention and preservation.
  • The End of Proprietary Software Recorded: Dec 8 2016 49 mins
    Merav Yuravlivker, Co-founder and CEO, Data Society
    Is it worth it for companies to spend millions of dollars a year on software that can't keep up with constantly evolving open source software? What are the advantages and disadvantages to keeping enterprise licenses and how secure is open source software really?

    Join Data Society CEO, Merav Yuravlivker, as she goes over the software trends in the data science space and where big companies are headed in 2017 and beyond.

    About the speaker: Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. She has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies and training. Merav manages all product development and instructional design for Data Society and heads all consulting projects related to the education sector. She is passionate about increasing data science knowledge from the executive level to the analyst level.
  • A Practical Guide: Building your BI Business Case for 2017 Recorded: Dec 8 2016 45 mins
    Ani Manian, Head of Product Strategy, Sisense and Philip Lima, Chief Development Officer, Mashey
    So you’ve decided you want to jump on the data analytics bandwagon and propel your company into the 21st century with better analytics, reporting and data visualization. But to get a BI project rolling you usually need the entire organization, or at the very least the entire department, to get on board. Since embarking on a BI initiative requires an investment of time and resources, convincing the relevant people in the company to take the leap is imperative. You’ll need to construct a solid business case, defend your budget request and prove the value BI can bring to your organization.

    In this webinar you’ll discover:

    - Why organizations need to invest in BI to begin with
    - How are organization deriving value from BI
    - How to build an internal business case for investing in BI
    - What are the intricacies of how to build a budget
    - How to drive your company to a purchasing decision
    - How to start realizing value from BI now
  • Containers: Best Practices and Data Management Services Recorded: Dec 7 2016 57 mins
    Keith Hudgins, Tech Alliances, Docker, Andrew Sullivan, Tech Marketing Engineer, NetApp, Alex McDonald, Chair SNIA-CSI
    Now that you have become acquainted with basic container technologies and the associated storage challenges in supporting applications running within containers in production; let’s take a deeper dive into what differentiates this technology from what you are used to with virtual machines. Containers can both complement virtual machines and also replace them as they promise the ability to scale exponentially higher. They can easily be ported from one physical server to another or to one platform—such as on-premise—to another—such as public cloud providers like Amazon AWS. In this Webcast, we’ll explore “container best practices” that discuss how to address the various challenges around networking, security and logging. We’ll also look at what types of applications more easily lend themselves to a microservice architecture versus which applications may require additional investment to refactor/re-architect to take advantage of microservices.
  • Analytics in the Cloud Recorded: Dec 7 2016 45 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    Today, data is everywhere. As more data streams into cloud-based systems, the combination of data and computing resources gives us today the unprecedented opportunity to perform very sophisticated data analysis and to explore advanced machine learning methods such as deep learning.

    Clouds pack very large amount of computing and storage resources, which can be dynamically allocated to create powerful analytical environments. By accessing those analytics clusters of machines, data analysts and data scientists can quickly evaluate more hypotheses and scenarios in parallel and cost-effectively.

    The number of analytical tools which is supported on various clouds is increasing by the day. The list of analytical tools spans from traditional rdms databases as provided by vendors to analytics open sources projects such as Hadoop Hive, Spark, H2O. Next to provisioning tools and solutions on the cloud, managed services for Data Science, Big Data and Analytics are becoming a popular offering of many clouds.

    Analytics in the cloud provides whole new ways for data analysts, data scientists and business developer to interact with each other, share data and experiments and develop relevant insight towards improved business processes and results. In this talk, I will describe a number of data analytics solutions for the cloud and how they can be added to your current cloud and on-premise landscape.
  • The Big BI Dilemma - Bimodal Logical Data Warehouse to the Rescue! Recorded: Dec 6 2016 59 mins
    Rick van der Lans, Independent Industry analyst, Lakshmi Randall, Head of Product Marketing for Denodo
    The classic unimodal data warehouse architecture has expired because it is restricted to primarily supporting structured data but not the newer data types such as social, streaming, and IoT data. New BI architecture, such as “logical data warehouse”, is required to augment the traditional and rigid unimodal data warehouse systems with a new bimodal data warehouse architecture to support requirements that are experimental, flexible, explorative, and self-service oriented.

    Learn from the Logical Data Warehousing expert, Rick van der Lans, about how you can implement an agile data strategy using a bimodal Logical Data Warehouse architecture.
    In this webinar, you will learn:

    · Why unimodal data warehouse architectures are not suitable for newer data types
    · Why an agile data strategy is necessary to support a bimodal architecture
    · The concept of Bimodal Logical Data Warehouse architecture and why it is the future
    · How Data Virtualization enables the Bimodal Logical Data Warehouse
    · Customer case study depicting successful implementation of this architecture
  • A World Full of Insights – Mapping & Geospatial Visualization with Your Data Recorded: Dec 6 2016 56 mins
    David Clement & Rick Blackwell, IBM Watson
    High performance and scalable data mapping offers unlimited opportunities for quickly categorizing and identifying key insights for retail, defense, insurance, utilities, natural resources, social sciences, medicine, public safety and more.

    Organizations, already awash in customer data, know geospatial capabilities can put a new “lens”on existing reports. Data from smartphones, GPS devices and social media has organizations anxious to factor in customer location, origin or destination, with time or day.

    Join IBM Product Marketing Manager David Clement and IBM Senior Product Manager Rick Blackwell and explore the new, world-class mapping and geospatial capabilities for IBM Cognos Analytics and Watson Analytics. Discover how you can add geographic dimension to visualizing critical business information in reports and dashboards in Cognos Analytics.

    Keywords:
    analytics, data, big, watson, ibm, visualization, mapping, geospatial
  • IT Powered Enterprise Analytics Recorded: Dec 6 2016 48 mins
    Andy Cooper, Enterprise IT Consultant, Tableau
    Traditional report factories are rapidly becoming obsolete. Enterprise organizations are shifting to self-service analytics and looking for a sustainable, yet long-term approach to governance that satisfies the needs of both the business and IT.

    The Business needs real-time access to data to drive critical decisions. IT needs to audit and manage data to ensure it’s accurate, secure, and governed to scale.

    With only eight percent of people in traditional organizations able to both ask and answer their own questions, it’s time to take a closer look at your analytics strategy.

    Join this webinar to take a closer look at enterprise analytics and learn how:
    · Visual data analysis brings speed, value, accuracy, collaboration and leads to culture of analytics

    · Modern enterprises are eliminating boundaries between IT and the business

    · Shifting to enterprise self-service analytic tools empowers both the business and IT
  • How is Data Analytics Reducing Payments Fraud? Recorded: Nov 30 2016 59 mins
    Ina Yulo (BrightTALK), Andrew Davies (Fiserv), Martin Koderisch (Edgar Dunn)
    Predictive Analytics and the study of Big Data has helped many institutions to detect fraudulent practices before they become a hazard to the business. This is especially evident in the Financial Services sector where deploying an efficient prevention and detection strategy is of utmost importance.

    Join this panel where experts will discuss:
    -Which analytics to look at to stop fraudulent payments in real-time
    -Using trends and behavioural analytics to detect anomalies
    -How to implement a holistic strategy that's right for your organisation
    -The challenges in maintaining compliance standards
    -Use cases and applications of analytics to prevent financial crime
  • Video interview: Big Data Challenges: What to do and where to go? Recorded: Nov 29 2016 6 mins
    Jason Foster, Director & Founder at Cynozure
    Listen to our interview at Big Data LDN with Jason Foster, Director & Founder at Cynozure.

    Jason will discuss:

    -The value of Big Data and which skills are required to deliver that value
    -How to get started with Big Data projects
    -What to do if progress is limited
    -Business opportunities around customer insight, supply chain analytics, and more
  • Video interview: Implementing a data-driven solution in the cloud Recorded: Nov 28 2016 7 mins
    Bobby Gill (Data & Digital Analytics Director at The Economist) and Sebastian Fabri (Analyst at Looker)
    Listen to our interview at Big Data LDN with Bobby Gill (Data & Digital Analytics Director at The Economist) and Sebastian Fabri (Analyst at Looker)

    The duo will discuss a successful case study on data-driven decision making.

    They will tackle:
    -How to implement data solutions quickly and efficiently in the cloud
    -What are the challenges of data-driven decision making?
    -How to discover data pain-points across an organisation and solve these accurately
    -The importance of real-time analytics in generating actionable insights
  • Video interview: Best practice tips for exploring and manipulating data Recorded: Nov 24 2016 4 mins
    Andy Cotgreave, Technical Evangelist, Tableau Software
    Listen to our interview at Big Data LDN with Andy Cotgreave, Technical Evangelist at Tableau Software.

    Andy will discuss:

    -Moving beyond dashboards and applying the “5 Whys” technique to data
    -Best practice tips for exploring and manipulating data
    -The need to think about “data exploration” as a task in itself, but as part of a person’s goal to make an impact on their business
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  • Live at: Mar 15 2016 12:15 pm
  • Presented by: Chris Bradley
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