Day 1 - 28 November 2018

Big Data Strategies

It all starts with data and leading the charge in digital transformation are data and analytics leaders. In order to become a data-enabled company, use game-changing AI and ML technologies and make informed business decisions, you need to know how to effectively collect, store, manage and analyse data. Day one looks at how to shape and implement Big Data strategies.

09:15AM

Big Data Strategies: Chairman’s Welcome

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09:30AM

Opening Presentation: Building a data and Analytics Strategy

Identifying game-changing advances e.g. predictive analytics and AI
Expanding your strategy

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10:00AM

Keynote: Delivering business value through Data Analytics

  • Accessing the power of unstructured data through machine learning
  • Creating business value and actionable insights from unstructured data
  • How images, video, speech and text can all be better recognised and processed
  • Key use cases and data sets that can benefit most from a ML approach
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10:30AM

Bill Yock

Chief Data Officer

Santa Clara County

Associated Talks:

10:30AM - Day 1

View Panel: Creating a data-driven culture

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Jessica Lachs

Head of Analytics

DoorDash

Associated Talks:

03:00PM - Day 1

View Lessons learned on experimentation and decision making

10:30AM - Day 1

View Panel: Creating a data-driven culture

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Panel: Creating a data-driven culture

  • Establishing evidence-based decision making as a core part of the digital workplace
  • Defining a clear strategy to leverage data whenever and wherever possible to enhance business efficiency and effectiveness.
  • Putting big data at the heart of your business
  • Closing the data literacy gap, hiring talent and getting buy in from the top.
. Bill Yock, Chief Data Officer, Santa Clara County
. Jessica Lachs, Head of Analytics , DoorDash
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11:15AM

Networking Break

11:45AM

Daniel Caraviello

Global Leader, Strategic Alliances & Talent Acquisition, Data Science & Informatics

Dow Agrosciences

Associated Talks:

11:45AM - Day 1

View Establishing and developing a highly competitive Data Sciences team

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Establishing and developing a highly competitive Data Sciences team

  • Getting the right skills balance – what new competencies are required?
  • Developing the leadership skills to catalyse data sciences adoption across the organization.
  • Employee engagement – approaches to boost retention of top data sciences talent.
. Daniel Caraviello, Global Leader, Strategic Alliances & Talent Acquisition, Data Science & Informatics, Dow Agrosciences
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12:15PM

Nav Kesher

Head of Data Sciences, Facebook Marketplace Experience

Facebook

Associated Talks:

12:45PM - Day 1

View Panel: Building an Effective Big Data Strategy

12:15PM - Day 1

View Making Sense of Unstructured Data

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Making Sense of Unstructured Data

Structured data only accounts for about 20 percent of stored information. The rest is unstructured data – includes texts, blogs, documents, photos, videos, etc. In this presentation, I will talk about *analytical methods and tools, to analyze unstructured data, *that data scientists may use to gather and analyze information that doesn’t have a pre-defined model or structure. Traditional analytical processes are not adequate to fully understand unstructured data an as such, I want to dwell on some of the newer methods such as semantic analysis and natural language processing to analyze unstructured data. I will talk about the best practices that has worked for me in my quest to untangle unstructured data as well as do shallow dives into Recurrent Neural Networks (RNN) and Convolutional Neural Networks and how deep learning is helping at identifying patterns in unstructured data.

 

. Nav Kesher, Head of Data Sciences, Facebook Marketplace Experience, Facebook
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12:45PM

Terry Rice

CEO and Founder

Epigen Technology Corporation

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Suqiang Song

Director and Chapter Leader for Data Engineering and AI

Mastercard

Associated Talks:

12:45PM - Day 1

View Panel: Building an Effective Big Data Strategy

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Nav Kesher

Head of Data Sciences, Facebook Marketplace Experience

Facebook

Associated Talks:

12:45PM - Day 1

View Panel: Building an Effective Big Data Strategy

12:15PM - Day 1

View Making Sense of Unstructured Data

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Panel: Building an Effective Big Data Strategy

  • What business problems are you trying to solve?
  • Data governance – what data to use, what other sources are there?
  • Bring together data, analytics, people and frontline tools to create business value
  • Dealing with legacy

 

Moderator: . Terry Rice, CEO and Founder, Epigen Technology Corporation
. Suqiang Song, Director and Chapter Leader for Data Engineering and AI, Mastercard
. Nav Kesher, Head of Data Sciences, Facebook Marketplace Experience, Facebook
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01:30PM

Networking Lunch

02:30PM

Afternoon Keynote: Making Big Data the centre of your business model

  • What problems is Big Data helping to solve?
  • What data will be used? How will it be generated and analysed?
  • How to encourage Big Data Innovation and stay ahead of the pack
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03:00PM

Jessica Lachs

Head of Analytics

DoorDash

Associated Talks:

03:00PM - Day 1

View Lessons learned on experimentation and decision making

10:30AM - Day 1

View Panel: Creating a data-driven culture

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Lessons learned on experimentation and decision making

. Jessica Lachs, Head of Analytics , DoorDash
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03:30PM

Panel: Big Data – Creating Intelligent Data Models

  • The increased need for big data analytics to drive AI & Machine learning
  • How to successfully unlock unstructured data & transform into learnable features
  • The advancement of self-service big data tools & its benefit for your organisation
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04:15PM

Dhruv Garg

Senior Software Engineer

Netflix

Associated Talks:

04:15PM - Day 1

View Solo: Scaling Business Insights on Over a Billion Connected Devices

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Tri Truong

Senior Data Engineer/Architect

Netflix

Associated Talks:

04:15PM - Day 1

View Solo: Scaling Business Insights on Over a Billion Connected Devices

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Solo: Scaling Business Insights on Over a Billion Connected Devices

Netflix users stream on a multitude of device platforms that have differing hardware and application characteristics. Characteristics such as operating system, hardware profiles, connected devices, and Netflix client versions can have significant effects on the user’s streaming experience. The Netflix Device History Service (DHS) is the scalable solution we built for tracking devices and their changing characteristics. This session will explain why DHS was needed to grow our business globally, go in depth on the architectural underpinnings, and describe the key analytic use cases DHS enables.

. Dhruv Garg, Senior Software Engineer, Netflix
. Tri Truong, Senior Data Engineer/Architect, Netflix
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04:45PM

The data centre of the future

  • Data centre hardware being built specifically for AI/big data workloads
  • Is your infrastructure up to the task?
  • How machine learning can help intelligently manage capacity
  • The continued rise of the software-defined data centre (SDDC)

 

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05:15PM

Session Close

Networking Party – 6pm – Hyatt Regency Hotel

An evening of networking on November 28 from 6pm. Access for Ultimate, Gold & Expo Plus holders in addition to speakers, sponsors, press and exhibitors. Taking place in the attached Hyatt Regency Hotel, join us from drinks, nibbles and networking at the Pool Area from 6pm. Further details to follow.  
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