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The Importance of being a Data Driven Company

Data-driven decision making is the only way to run a company. It allows us to make fast, smart decisions and stay on top of our market. In this webinar David will discuss how you how you can use real-time data to understand your market, product and team.
Recorded Sep 17 2014 39 mins
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Presented by
David White, Founder and CEO of import.io
Presentation preview: The Importance of being a Data Driven Company

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  • Using ML to reduce cloud spend Dec 16 2020 6:00 pm UTC 30 mins
    Ziv Pollak, Sr Cloud Strategy Manager, TELUS
    One of the main reasons to move to the cloud is reducing costs and saving money. Adversely, the ease of provisioning additional costly resources on the cloud necessitates the need for tight spend control. Without this control, cloud migrations will not achieve its business goals and fail. Basic cost control can be achieved using simple reports, spend alerts and force-shutting-down of runaway projects. The next level of cost control includes storing details billing data and then using this data to: Build dashboards that allow visualizing different aspects, Build ML models to predict future spend, Analyze what-if scenarios to reduce future costs.

    About the presenter:

    As a member of TELUS's Cloud Center of Excellence, Ziv is advancing cloud adoption by building hardened, ready-to-go patterns that ensure security, reliability, operational and cost-efficiency.
    Ziv started his career as a software developer and now has over 20 years of experience in the IT world, leading development teams and bringing complex projects from concept to production.
    His current focus is on enabling the development of cloud-native applications and allowing the organization to get the full benefits of the cloud.

    Ziv holds a Ph.D. from Tel Aviv University, specializing in machine learning.
  • The 10 Vs of Big Data Dec 15 2020 10:00 pm UTC 60 mins
    George Firican, Founder of LightsOnData.com
    The term “Big Data” can be a bit misleading as it’s making us focus on its size and miss the most important nature of the medium, and that’s its complexity. We’ve all heard about its volume, velocity and variety attributes, but what about its other defining characteristics? Join us for an eye-opening session to get a new and empowering perspective of Big Data, its 10 Vs, risks and how to mitigate them, while discovering its benefits and immense potential through real-world applications.

    Key takeaways:
    • A better understanding of big data's characteristics
    • The challenges and risks of big data and how to mitigate them
    • Real examples on how different organizations use big data to their advantage

    About the speaker:
    George Firican is an exuberant advocate for the importance of data, a frequent conference speaker and a YouTuber, being ranked among Top 10 Global Thought Leaders and Influencers on Digital Disruption and Top 15 on Innovation and Big Data. His innovative approach to data management received international recognition through award-winning program and project implementations in data governance, data quality, business intelligence and data analytics. In his spare time, he loves to create informative, practical and engaging educational content, and help organizations get more visibility on social media. George is also the proud founder of LightsOnData.com.
  • Through the Fog and Beyond the Edge: Cloud Analytics for New Hybridity Practices Recorded: Sep 15 2020 60 mins
    Jérémie Farret, Vice President Advanced Analytics and A.I., Inmind Technologies
    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 | Farrid Zeighami, Virgin Orbit | 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?

    Join this webinar to learn:
    - How the community has grown and evolved
    - What topics are trending within our audience of BI & Analytics professionals
    - What to look forward to in 2020
  • 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.

    About the speaker:
    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
    Shailesh Mangal, Vice President – Engineering, Roambee
    In an increasingly digitally connected world with abundant data sources, manufacturers and logistics companies need even more efficient ways to make effective supply chain decisions in real-time.

    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?

    In order to truly empower your supply chain with data that you can trust, decipher in seconds, use “right then & there,” and act without further need for analysis, you need Artificial Intelligence (AI) to provide a “business-friendly view” of location and condition data that’s collected in the field.

    Join this webinar to learn how AI will provide a business-friendly view of your goods and assets monitoring data, and also play a crucial part in assimilating and instantly validating important data points across multiple data streams for faster and better decision-making.

    About Shailesh Mangal, Vice President – Engineering, Roambee:

    Shailesh Mangal is Roambee’s Vice President of Engineering. He is responsible for the ensuring excellence in the development, performance, and quality all Roambee platforms and applications.

    Shailesh has been developing enterprise and web applications for more than 20 years. His passion spans from nurturing highly productive and agile development teams to steering through fast-paced ever-changing development landscapes and maintaining code quality & performance. His main areas of interest include object-oriented design, system and cloud architectures, big data, real-time search, and analytics.
  • 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
  • Building Data Science Organization with Business Impact in Mind Recorded: Jun 11 2020 60 mins
    Mikheil Nadareishvili, Mariam Lelashvili, and Levan Borchkhadze, TBC Bank
    Data Science has reached a point of maturity in large organizations. Having proven its value on fascinating niche use cases, it is now on every executive’s mind and ready to radically transform business-as-usual processes. But in order to pull off the transformation, the organization and method of delivery of analytics must change first. Data scientists should transform from isolated “unicorns” to being part of well-thought-out value delivery process.

    We will discuss how we at TBC made the organizational change, the use cases which were made possible through it and what kind of results were achieved. We will talk about lessons learned by the example of two of our successful use cases: digital affluent value proposition, and next best offer.

    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
  • The Advanced Analytics Landscape: Architecture and Tools Recorded: Jun 11 2020 47 mins
    Javier Correa, Head of Advanced Analytics & Big Data, Analytics10 Chile & México
    In this talk, you will learn different types of architectures for multiples use cases, and the main tools to build and develop your analytics apps.

    Architectures for:
    - Elasticity
    - Predictive inventory
    - Recommendation Systems

    And the best tools to deploy them fast, accurate and governed.

    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.

    At A10, Javier is responsible for ensuring the success of the most important clients in Chile and México, producing deep business insights generated through sophisticated analytics, that it's translate into impact at scale through 4 principals skills: business analytics, technology, engineering and mathematics.
  • Patient Centricity and the Future is Now Recorded: Jun 10 2020 120 mins
    Richard Maguire, Chief Data Scientist, MDGroup
    The democratization of clinical trials is disruptive and that’s a good thing. Join this talk with MDGroup's Chief Data Scientist Richard Maguire as he discusses:

    Managing the Big Data Wave

    - Performant Infrastructure not only to manage the data size and types, structured & unstructured, but to manage Compute at Scale
    - A Data Lake allows you to manage the wave of data by capturing all of it
    - Next step is to store data in a proper data store for data type and ensure that the data is clean
    - Then, you need to analyze the data for decision making

    Managing the Big Textual Data that is Usually Forgotten

    - Textual Data is Normally Siloed, not because it is unimportant, but because many do not know how to manage it
    - Natural Language Processing (NLP) uses linguistic and semantic parsing to uncover patterns that can be deployed in predictive analytics

    COVID-19 has Accelerated Move to Virtual Trials & Wearable Sensors: Disruptive Event & Technology

    - Major Benefit is Continuous Patient Sensor Data, so NOT Episodic
    - This means making correlations and predictions more accurate
    - The challenge is the size of this data stream as it can become a tsunami
    - Data Management and Data Cleaning are Paramount
    - Virtual Clinical Trials: The Future is Here Now

    Richard Maguire is presently the Head, Data Science, mdgroup and is tasked with bringing predictive analytics into their patient primary offering via their Primarius mobile app and patient portal. With a background in predictive analytics and Natural Language Processing, Rick has worked to bring wearable sensors into a Healthcare IoT for clinical trials. He has been a Subject Matter Expert at Oracle for Predictive Analytics and Predictive Genomic Medicine as well as Real World Data/Evidence for a global IT provider. Experience as a Director of Clinical Diagnostics in Pathology for a very large comprehensive cancer centre.
  • Practical AI: Predicting Business Outcomes with Analytics Recorded: Jun 10 2020 61 mins
    Tomasz Smolarczyk, Spyrosoft | Puravee Bhattacharya, Energia | Matt Shubert, Experian
    Join the conversation as industry experts discuss how businesses are taking advantage of predictive analytics technology to gain a competitive edge in the marketplace.

    You'll discover:
    - Use cases that show how AI and machine learning are helping companies be more proactive than ever
    - How predictive modeling can lead to more informed business decisions
    - What steps organizations can take to adopt an AI-enhanced analytics strategy that works for them
    - And more!

    Moderator: Tomasz Smolarczyk, Head of Artificial Intelligence at Spyrosoft
    Panelist: Puravee Bhattacharya, Senior Data Scientist and Analytics, BI & Performance Reporting at Energia
    Panelist: Matt Shubert, Director of Data Science and Modeling at Experian
  • AI in Grundfos: Production Advances in Business Domains Recorded: Jun 10 2020 43 mins
    Lishuai Jing, Senior Data Scientist Analytics and AI group, Grundfos, Denmark
    Being historically a manufacturing company, Grundfos aims to bring digital transformation into its core business. This radical move not only bring challenges, but also energizes a wave of exploring/adopting state-of-the-art cloud computing, machine learning and AI technologies that impact different business domains. The new advances in computing platforms and machine learning services brings convenience to productionize industrial intelligent solutions. However, practical obstacles are hindering the scaling capability.

    This talk will take you to peek into some of the challenges that are faced in researching and deploying AI solutions within Grundfos. I will give you a picture on Grundfos’s digital initiatives landscape and our hands-on experience on scaling AI solutions that accelerates enterprise level adoption. Two concrete use cases in sales and marketing and supply chain management can shed some light on how business value, agile development, DevOps, data science, and MLops together enable success in business value creation. In particular, I will address the data challenge and the statistical methods, machine learning/deep learning techniques that are adopted to solve some real life challenges.

    About the speaker:
    Currently, Lishuai Jing is working with advanced statistical inference methods, machine learning and deep learning techniques, and general AI in the largest pump manufacturing company. He has a PhD diploma in statistical signal processing and wireless communication from aalborg university, Denmark. Before joining Grundfos, he was a researcher on 4G/5G and IOT communication technologies. He advocates data and AI-driven approach to improve business intelligence, operating efficiency, productivity and customer satisfaction.
  • Data Governance and The Art of the Fugue Recorded: Jun 9 2020 46 mins
    Randy Gordon, Data Governance Leader
    Elaborating on his article, "Data Governance and The Art of the Fugue," Randy will guide the audience through a layperson's explanation of what a fugue is, using J.S. Bach's The Art of the Fugue as an example, and draw parallels between its structure and that of data governance frameworks. Today’s data, in its near-infinite variety of sources and types, resembles polyphonic music such as fugues more so than homophonic music like popular songs. But combining independent melodic lines is just as difficult as understanding disparate data sets.

    Without some guidelines, the result is cacophony, when sounds combine with no rhyme or reason, and the ear hears nothing but harshly clashing noise. In the data world, we have the same situation when data lakes become data swamps, filled with in-comprehensive information not fit for any use, because of the lack of data governance.

    Randy will also explore these ideas:
    - How the subject of the fugue provides the listener guideposts similar to how metadata and lineage help analysts navigate data
    - How following the fugue "governance framework" allowed Bach to compose with enormous inventiveness while still providing his listeners a transparent structure even with many moving parts
    - How a similar approach to creating a data governance can fuel innovation

    In conclusion, Randy will demonstrate how this musical perspective can enable a rethinking of the very goal of data governance, a goal extremely relevant to the world of exploding, ever changing data we live in today.

    About the speaker:
    Randy Gordon is a data governance professional with over 10 years of experience in leadership roles in financial services. Most recently, at Moody’s, Randy established their first formal data governance program, building the data governance framework, principles, standards, and organization.
  • Melee of Data Catalog to MLOps Mechanisms: DataOps for Actionable Analytics Recorded: Jun 9 2020 50 mins
    Pragyansmita Nayak, Ph.D., Chief Data Scientist, Hitachi Vantara Federal
    The melee of raw data in the various forms of structured, unstructured and semi-structured data has its own unique challenges. Extracting the hidden nuggets of information to meet the vision and aid the strategic and tactical goals of an organization is a resonating objective of every stakeholder today. This requires a number of systematic, both synchronous and asynchronous processes and techniques to rhythmically accomplish the objectives in a transparent manner. Data driven process enablement and the resulting effective decision making starts from scratch - identification of the most relevant and related data assets, posing the business problem, determining the analytics components.

    The solution should ideally be as reusable as possible in order to aid related problems resolution down the road; aiding the knowledge growth, process automation and the effective business and data interplay. The overarching goal needs to be to complete this unique jigsaw puzzle specific to every individual organization; fitting as comfortably and seamlessly as one wants their hands to fit in a pair of gloves.

    This talk will focus on how the DataOps mechanisms such as data catalogs, data lineage and, data fusion leading to near-transparent self-service analytics and MLOps enable and enhance advanced actionable analytics outcomes.

    About the speaker:
    Pragyansmita Nayak is Chief Data Scientist at Hitachi Vantara Federal (HVF), a wholly owned subsidiary of Hitachi Vantara. She has over 20+ years of experience in software development and data science-related research and development. She holds a Ph.D. in Computational Sciences and Informatics from George Mason University (GMU) and Bachelor's degree in Computer Science from Birla Institute of Technology and Science (BITS), Pilani, India. Her Ph.D. thesis focused on the application of Machine Learning techniques such as Bayesian Networks for redshift estimation.
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.

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  • Title: The Importance of being a Data Driven Company
  • Live at: Sep 17 2014 9:00 am
  • Presented by: David White, Founder and CEO of import.io
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