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Video interview: How to make the most out of your data

Listen to our interview at Big Data LDN with Sean Jackson, CMO at EXASOL AG.

Sean will give an overview of how you can get the most out of your data -- from cloud-based analytics to data visualization, Sean will break down the challenges you face in your quest to become a data-driven professional.
Recorded Nov 15 2016 5 mins
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Presented by
Sean Jackson, CMO, EXASOL
Presentation preview: Video interview: How to make the most out of your data

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    In this webinar, you will learn how Sysco leverages Alation for:

    - Intuitive data search and discovery
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    Gary Gruccio, Director of Enterprise & Market Analytics and Ian Reed, Manager Enterprise Analytics at Signet Jewelers
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  • Big Data: Tactics For Managing Legal Risks in the Operation & Sale of a Business Dec 15 2020 4:00 pm UTC 45 mins
    Myron Mallia-Dare, Corporate & Technology Lawyer, Miller Thomson LLP
    Organizations are relying more on data and technology to operate their business and differentiate their products. As such, managing the legal risk that arises from this data-driven world is critical when operating or selling a business. These unique issues a magnified when big data is utilized along with certain emerging technologies such as artificial intelligence.

    We will discuss some of the legal issues that arise and how organizations can protect their business and it’s valuation on exit. We will provide strategies on how to manage third party risk, address intellectual property and infringement issues and how to comply with data security and privacy laws.

    Myron is a corporate lawyer at Miller Thomson LLP in Canada. He has significant experience in the technology sector. His practice focuses on domestic and international mergers and acquisitions, venture capital, corporate finance and provides strategic support for emerging growth companies (startups). He advises on complex technology transactions in the areas of artificial intelligence, cloud computing, FinTech, cybersecurity and blockchain. He focuses on providing responsive, creative and customized advice that aligns with his clients’ goals. Myron routinely writes and speaks at various conferences on topics relating to emerging companies and technologies, such as AI, FinTech and cybersecurity. He has co-authored chapters of books written by global leading experts in the areas of AI and Cloud computing.
  • Rethinking Data Governance and Data Integration for a cloud-based digital world Dec 15 2020 1:00 pm UTC 30 mins
    Kat Holmes, Global Director of Data Governance at Travelex
    Within the Data Revolution there has been a lot of focus on Data Governance in the last couple of years for two reasons: Value and importance of data and analytics to a company’s business strategy has grown exponentially. And regulatory change globally means it can’t be pushed aside.

    Data Governance has been around a long time, especially in financial services, but how should the capability change to keep up with the following trends in data and technology?

    * Cloud based infrastructure, applications and data platforms

    * Digital technologies

    * AI technologies, both in data and more broadly

    * Laser focus on the customer experience and outcomes

    Many companies are struggling with the dichotomy between: Needing to build agile data and analytics capabilities that can rapidly deliver value to the business. And needing to ensure the data in these use cases is governed - compliant to an ever-increasing complex regulatory environment, and also trusted and accurate.

    To resolve this dichotomy data governance needs to change to be aligned to the new paradigms in data and technology.  

    We will talk a bit more about the relationship between Data Governance and Data Integration/Data Engineering in this new way of thinking.

    Let’s recap what rethinking Data Governance and Data Integration means:

    -Embedding Data Governance into the operating model for analytics use case delivery.

    -Implementing AI enabled technologies to run data governance, to be lean and fast.

    -Focussing firmly on enabling safe innovation rather than compliance.

    -Use industry standards not bespoke models that are costly to develop and maintain.

    -Work towards real time data integration, transforming and governing the data in the data platform.
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    Dirk Hofmann, Co-Founder and CEO at DAIN Studios
    Data and AI adoption calls for strong determination and persistence from the leadership. It should be on the agenda for leadership meetings from the board, the C-suite to senior managers. “We observe that fully committed leadership has been one of the common denominators for success in digital transformation and becoming a data-driven company”.

    Dirk Hofmann, co-founder and CEO of DAIN Studios Germany will talk about this and other findings that we have made in the course of more than 40 Data and AI initiatives with different companies and industries in Europe.

    You will hear concrete and practical recommendations on:
    · setting your ambition level by creating a data and AI vision, and identifying the most lucrative data opportunities
    · building your data asset and data governance models
    · defining the solution architecture that covers end-to-end use cases for machine learning applications
    · hiring the right people for both technical and business related roles, highlighting the key role of an AI strategist for getting business impact
    · setting up the data and AI organization and operating model that fits the maturity of the company

    During the course of the talk, Dirk will bring practical examples from the companies we have worked with in insurance, aviation, telecommunications, consumer goods and other sectors.
  • 5 A's to Big Data Success (Agility, Automation, Accessible, Accuracy, Adoption) Dec 15 2020 9:00 am UTC 45 mins
    Sumesh Nair, Enterprise Architect - Data Strategy & Architecture at Tata Consultancy Services
    Big Data & Analytics is transforming to Big Data "for" Analytics where the lines are blurring between Data Management principles & Self Service driven Analytics architecture with emphasis on Automation. This session will give you focused approach to the five A's for Big Data Success for every Analytics driven organization advocating freedom to "citizen analysts" or "citizen data scientists" with a balance on cost & security; with a flavor of Azure Cloud. Here we are considering that most organizations have already adopted a Cloud Journey & Agile operating model is a de-facto.

    Key Takeaways:
    We will go through some practical scenarios on each of the 5As with an eye for infrastructure cost, security & compliance
    - Agility - Data Agility is when your data can move at the speed of your business needs. We will go through some considerations on how to achieve need for speed through different technologies like CDC, APIs, IoT, Kafka & self-service model of data sharing & reporting. Also, how to build a framework to stimulate Innovation to stay ahead of the curve
    - Automation – A Stitch in Time Saves Nine. Industry is moving ahead from IAC & CI/CD being an afterthought to automation first approach
    - Accessibility - Provisioning access to ERP/Source system data is priority#1.
    - Accuracy - Data Quality should be at the heart of your ecosystem as it is most needed to gain business trust, we will touch upon key levers & design methods to implement it
    - Adoption: Data Marketplace - How can I sell my data should be the first question that should strike your mind before investing effort to bring data. How to prioritize the right data elements & how to increase adoption by giving visibility through Data Catalog, Ontology, & APIs. We will also go through methods of introducing self-service data science sandbox for experimentation to increase for citizen data scientists.
    - Cost, Security & Compliance - Infrastructure Cost, Security & Compliance cuts across all the 5 A's.
  • The rise of automated analytics and the demise of dashboards Dec 15 2020 9:00 am UTC 60 mins
    Bhavika Unnadkat, Head of Data at Momentum Energy
    Automation can deliver insight continually, because live data can be analysed in the background all the time. The need for a long and painful process to manually investigate events which had already occurred is removed, and machine learning continually fine tunes its search for meaningful, relevant signals. The result is personalised delivery of insight, to the right person at the right time – in language they can understand.

    -Dashboards Present Data, Not Recommendations
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    -There’s Room for Misinterpretation
    -Go Beyond Simply Explaining Your Charts
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    Hybrid Computing, and thus Hybrid Analytics are concepts which are undergoing accelerated mutations, with the introduction of Edge and Fog Computing, in the wake of new mobility and IoT communication protocols, technologies and practices being phased in the Industry on a daily basis, 5G being its latest illustration. Our objective will be to shed some light on the various impacts, both positive and challenging, that these transformations impose on Cloud Analytics.

    This session will first address what these changes spell out for Cloud Analytics and in particular, what are the new considerations, key assets and enabling paradigms being introduced, both in terms of functional architectures and underlying infrastructures supporting the ingestion, distributed treatment and produced insights, in the cloud, in the fog, and at the edge, along with the unlocked potentials but also the pitfalls associated to them.

    As a part in these considerations, the session will address the intrinsic security, information privacy and data protection concerns, and the specific hybrid specificities which allow for new ways to compartment privacy and protect anonymity while maintaining the same descriptive and predictive capabilities. Unfortunately, we’ll see that these new hybrid architectures can also harbor new combinations of vulnerabilities.

    The session will then introduce the invariants of Cloud Analytics and put them in perspective with the previous transformations. In the wake of such changes, some traditional practices still apply and suffer little or even no changes from the introduction of Edge and Fog Computing paradigms.

    Finally, some illustrations will be given, using real world, in production implementations in the telecommunication industry. Q&A will follow.
  • How Cloud Providers Enable Full Stack Data Science Recorded: Sep 10 2020 37 mins
    David Yakobovitch, Principal Data Scientist, Galvanize
    A Primer into Global Cloud Software

    End-to-end advanced analytics and data science can scale with continuous cloud systems across the globe. From AWS and Azure to GCP and Alibaba Cloud, listen in as David shares his take on tools and tips from these cloud providers to bring your products to market.

    About the presenter:
    David Yakobovitch is a Data Science Team Lead at Galvanize, responsible for delivering Scaled Training Programs. He partners with Engagement Managers and Account Executives as a Technical Expert for Pre-Sales and Product Marketing.

    David currently serves as an advisor for The Carpentries, Futureworks, CUNY Startups, and MaiiC. David is the Host of HumAIn Podcast, focused on AI, Data Science, Future of Work and Developer Education. (www.humainpodcast.com)

    David previously served as Lead Data Scientist for Enterprise with General Assembly in 2017 and 2018, for the Fortune 500 portfolio. General Assembly was acquired by Adecco for $413 million in 2018. Prior to General Assembly, David served as Chief of Staff for the BIG3 Basketball League from 2016 to 2017. Prior to BIG3, David served in a variety of roles in Banks and Insurance Providers from 2010 to 2015, including Citigroup, Deutsche Bank, ADP, and Aflac.

    David grew up in the United States. He received an undergraduate degree in business administration and information systems from University of Florida and is pursuing a PhD in Advanced Research at Capitol Technology University.
  • Best Practices for Streamlining Your Cloud Analytics Initiative Recorded: Sep 10 2020 60 mins
    Nicholas Manolakos, Rogers Communications | Barney Walker, Independent | Venu (Vidya) Vidyashankar, Heartland Payments
    Advance your knowledge of the latest tools and best practices that industry experts recommend to simplify and accelerate your approach to cloud analytics for the enterprise.

    You'll come away with:
    - How to determine the best approach to adopting a cloud data architecture that works to meet your needs
    - Tips and tricks for streamlining data governance in the cloud to ensure high data quality for insights
    - A better understanding of what a robust cloud analytics strategy can accomplish for you and your organization
    - and more!

    Nicholas Manolakos, Sr. Enterprise Architect, Enterprise Platforms and Governance, Rogers Communications
    Barney Walker, Advisor / Data, Technology & Operations Leader, Independent
    Venu (Vidya) Vidyashankar, Senior Manager, Enterprise Data Architect, Heartland Payments
  • Why and how to start with a strategy before moving directly to cloud Recorded: Sep 10 2020 26 mins
    Özgür Kaynar, General Manager & Founding Partner, Analythinx
    Moving to the cloud looks easy, but in reality not all vendors and features are at the same level of maturity and capability.

    Going with just cost and ease of installation/set up criteria most of the time fails or brings some disappointment when things gets complex and more dense.

    With a trusted advisor perspective, don't start with cloud options and features, instead start with:

    - Understanding business strategy and mission of the company
    - Business value cases which would be gathered with data and analytics
    - Crosscheck with architecture / IT teams
    - Evaluate cloud vendors based on facts and solid use cases

    We at Analythinx have developed an evaluation tool which could be used through this kind of strategy and roadmap work for any company seeking a short or long term cloud strategy.

    About Ozgur Kaynar:
    Ozgur is a senior executive with 25+ years of technology and consulting experience, deep focus on setting up Data & Analytics Strategy for companies, helping business organizations to leverage data as a strategic asset and achieve high business value with agile advanced analytics and proper governance models.
  • Lake to Pond to Puddle – a purpose oriented Data Platform design framework. Recorded: Sep 8 2020 27 mins
    Prajesh Kumar Sugumaran, Vice President, Global Head of Analytics Engineering, Affine Analytics
    When the data is well organized, intelligence is not that hard to find. Learn how to architect a data platform that will accelerate an org’s ability to extract intelligence with minimal effort.
  • Optimizing Your Cloud Architecture for Analytics Recorded: Sep 8 2020 45 mins
    Ivan Roche, Disguise | Budiman Rusly Djohari, Sequis | Suzanne Cashman Rain, RR Donnelley
    Join the conversation as industry experts take a deep dive into the latest advice for building a big data ecosystem tailor-made for analytics.

    You'll discover:
    - The necessary components required to design a cloud architecture that supports analytics projects for business use cases
    - Key principles behind successful data management for analytics initiatives to ensure quality insights
    - Common challenges organizations face when taking analytics to the cloud, and how to overcome them
    - and more!

    Ivan Roche, Global Head of Business Intelligence & Technology, Disguise
    Budiman Rusly Djohari, Chief Data & Analytics Officer, Sequis
    Farrid Zeighami, Sr. Enterprise Data Architect, Virgin Orbit
    Suzanne Cashman Rain, Director, Analytic Innovation R&D, RR Donnelley
  • Bringing true analytics value to Boardroom – but how? Recorded: Sep 8 2020 47 mins
    Asko Kupiainen, Director, Products and Services, QROi Analytics
    Making business analytics can be paradoxically challenging. Having data alone, even with clear actionable insights, will not be enough for dynamic business needs of 2020's. On one hand there is need to know what to analyze and act fast according to insights. On the another hand there is always uncertainty; do we have the right data basis for capturing the real value, is this important enough, what is the business impact.

    Management teams are having tough call to rely on right information being at hand. More often than not, that means further insights, further actions, yet another analysis, various business cases, leading to time lost, endless (remote) meetings, new reviews and finally opportunities vanishing.

    Things could be different, though.

    In this presentation, we’ll discuss how to bring the real value to boardroom through monetized business analytics. With directly commercialized analytics, critical aspects are prioritized by real value created, payback times covered, with business impacts readily available. All that in common boardroom language - money.
  • Q2 2020 Community Update: Business Intelligence & Analytics Recorded: Jun 30 2020 23 mins
    Erin Junio, Content Manager (BI & Analytics Community), BrightTALK
    Who is in the BrightTALK BI & Analytics community, what topics are of most importance to them, and what type of content do they prefer?

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  • Winning with Data Science for Executives Recorded: Jun 11 2020 48 mins
    David Yakobovitch, Data Science Team Lead, Data Partnerships, Galvanize
    Why is a data-driven strategy essential for the success of your business? Data Science has come so far recently, but why? What industry trends are impacting the Data Science and AI industries? David explores common language to demystify data science, he reveals where companies are today in Data Maturity, and he articulates what data opportunities exist for companies to become data-driven.

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    David Yakobovitch is a Principal Data Scientist at Galvanize, responsible for delivering Global Instruction, Scaled Training Programs, and Customer Success. He also partners with Engagement Managers and Account Executives with Pre-Sales and Product Marketing. David hosts the HumAIn Podcast, a Top 100 Technology Podcast on Artificial Intelligence, Data Science, Developer Education and Future of Work (www.humainpodcast.com). Prior to Galvanize, David led Enterprise programs at General Assembly (Bloomberg and Booz Allen Hamilton). Prior to GA, David worked in the financial services industry with banks, quantitative firms, and alternative data providers including Citigroup, Deutsche Bank, ADP, Aflac, Intel, and IBM Watson.
  • How to Unlock Logistics & Supply Chains with Artificial Intelligence Recorded: Jun 11 2020 37 mins
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    How do you overcome the delays in analyzing real-time data? How do you translate that to better understand supply chain and distribution risks? How do you reduce the time to decide the best course of action and act on it?

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  • Trends in Advanced Analytics and Data Science Recorded: Jun 11 2020 60 mins
    Lishuai Jing, GRUNDFOS | Dan Darnell, H2O.ai | Pragyansmita Nayak, Hitachi Vantara Federal | Paul Kowalczyk, Solvay
    Stay up-to-date on the latest tools and best practices that industry experts recommend in order to get the most value out of your advanced analytics and data science strategy.

    You'll come away with:
    - A better knowledge of the technology on offer to help scale your organization's approach to advanced analytics and data science
    - Key factors to consider when adopting an advanced analytics solution
    - Best practices for implementing a data science program and advanced analytics strategy that works for you
    - And more!

    Moderator: Lishuai Jing, Senior Data Scientist at GRUNDFOS
    Panelist: Dan Darnell, VP of Product Marketing at H2O.ai
    Panelist: Pragyansmita Nayak, Chief Data Scientist at Hitachi Vantara Federal
    Panelist: Paul Kowalczyk, Senior Data Scientist at Solvay
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    Mikheil Nadareishvili, Mariam Lelashvili, and Levan Borchkhadze, TBC Bank
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    Presented by:
    Mikheil Nadareishvili, Deputy Head of BI, TBC Bank
    Mariam Lelashvili, Analytical Transformation Project Leader, TBC Bank
    Levan Borchkhadze, Senior Data Scientist, TBC Bank
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    - Elasticity
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    - Recommendation Systems

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    About the speaker:
    Javier Correa is a commitment and Enthusiast leader of Advanced Analytics & Big Data transformation projects, with verified success in executing high impact transformation in diverse industries. He also sells this type of project and the necessary tools to develop these projects.

    Javier adds value to organizations as an analytics translator, using my knowledge in AI and Analytics to guide business leaders to identity and prioritize their business problems to get the RoI on solving those problems or opportunities.

    He plays a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontlines. He translates to business the potential of analytics and to data professionals the way that they must build the solutions to create value, supporting from the data extraction and the architecture, to the knowledge in building models to solve problems with data.

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Managing and analyzing data to inform business decisions
Data is the foundation of any organization and therefore, it is paramount that it is managed and maintained as a valuable resource.

Subscribe to this channel to learn best practices and emerging trends in a variety of topics including data governance, analysis, quality management, warehousing, business intelligence, ERP, CRM, big data and more.

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  • Title: Video interview: How to make the most out of your data
  • Live at: Nov 15 2016 12:00 pm
  • Presented by: Sean Jackson, CMO, EXASOL
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