PAST EVENTS

Data / Analytics Strategies

Strategies to help leverage full value from your design and implementation of an effective Business Intelligence / Analytics / Big Data framework.

November 21, 2019

9:00am-5:00pm

7 CPE / 0.7 CEU / CISSP / 7 PDU Credits Awarded

Conference location: Donald E. Stephens Convention Center Rosemont (O’Hare) Illinois

Overview

Data is the lifeblood of every business, but to empower the organization, it needs to be used carefully and strategically. How can IT leverage BI initiatives to become a stronger partner and ally to business units? What pitfalls should be avoided?

What You Will Learn

In this one day conference attendees will learn:

• Accelerating Transformation & Adapting to the Business
• Accelerating the Evolution of Data Analytics
• How to Build a Modern Data Analytics Platform
• Developing Data Literacy within your Organization
• The Last Mile: Designing a Presentation Layer that Delivers
• Make Your Next Data Warehouse Your LastStrategic Roadmap for BI and Analytics
• Designing Big-Data Platforms for an Enterprise

Conference Price: $289.00 per person

Each attendee will receive a certificate awarding 7 CPE credits for CISSP continuing education, in addition to 0.7 CEUs and 7 PDUs. CISSP is a registered certification mark of (ISC)², Inc.

8:00am – 9:00am: Registration and Continental Breakfast

9:00am-9:50am: Accelerating Transformation & Adapting to the Business

Louis Caron, Global Enterprise Architect, Office of the Global CTO, Hitachi Vantara

Enterprise IT has a great opportunity to for align their initiatives with business objectives to drive business growth.

In this session attendees will learn how to:

• How they should think BI/Analytics in the context of Digital Transformation
• Understand and influence the key ingredients of innovation
• Apply innovation into strategy based on business objectives
• Involve key elements of business strategy with various influencers and stakeholders
• Align enterprise IT data strategy to business strategy

Caron

9:50am -10:20am: Refreshment Break

10:20am-11:10am: Accelerating the Evolution of Data Analytics

Hunter Almgren, Chief Technologist, Hewlett Packard Enterprise

When, where, and how we analyze data is changing at a rapid pace. The ability to analyze new types of data along with existing data sets at the speed it’s generated presents challenges from edge to core. Employing advanced analysis techniques such as machine learning, along with the creation of a consistent data pipeline, are foundational to a modern data strategy. Come learn about new ways of addressing these data challenges.

Almgren

11:10am-12:00pm: How to Build a Modern Data Analytics Platform  

Fred Bliss, CTO, Aptitive

Data Lakes vs Data Warehouses, batch vs. real-time streaming, buy vs. build – the explosion in hybrid and cloud-native offerings has given enterprises the opportunity to revolutionize the way they manage and analyze data. Without a ‘one-size fits all’ approach available, however, navigating the landscape and making the right technology and architecture decisions can be an overwhelming undertaking.

In this session, Aptitive will help guide you through the components of a modern data platform and help provide a roadmap toward understanding the pros, cons, and trade-offs of various technology and design decisions in the enterprise data space.

Bliss

12:00pm-12:50pm: Developing Data Literacy within your Organization

Greg Woodard, Principal, Solve

It is estimated that fewer than one-third of business users can confidently understand, analyze and argue with data. In many organizations, many decisions are gut-based decisions even though there is data available to help with the process.

Data literacy empowers everyone to ask questions of data, build knowledge, make decisions and communicate its meaning with others.

During this presentation, we will cover the importance of data literacy and how to begin on a data literacy journey for yourself and your company.

Woodard

12:50pm – 1:50pm Luncheon

1:50pm-2:40pm: The Last Mile: Designing a Presentation Layer that Delivers

Jason Bean, Vice President, BI & Analytics Practice Leader, Messina Group Consulting

Often taken for granted as the last, simple piece to the puzzle, the presentation layer can make or break the value proposition of your analytics program. Messina Group will guide you through a success plan for your presentation layer, including:

• Aligning with the business for adoption and engagement
• How to identify, deliver and measure value creation
• Architecting purpose-built datasets to support use cases
• Simplifying advanced analytics use cases to promote value added behaviors and decisions

Bean

2:40pm – 3:10pm: Refreshment Break

3:10pm-4:00pm: Make Your Next Data Warehouse Your Last

Bruce McCartney, Senior Data Vault Architect, PerformanceG2, Inc.

If your reading this, chances are you have a belief in the value of data warehouses and analytics; in fact, you probably already have a form of a data warehouse that may not be meeting your needs. The purpose of this presentation is to discuss the reasons why many data warehousing initiatives fail, and how the Data Vault 2.0 “system of business intelligence” deals with these issues so that your next data warehouse initiative will be your last. Most of my Data Vault projects, and those of the many of the students in data vault certification training, are replacing ‘failed’ data warehouses. These are often referred to as modernization, or next generation, or 2.0, etc. but are essentially “do-overs”. If you are about to embark on a greenfield data warehouse, congratulations – and let’s avoid these common pitfalls and build a foundation that will last using Data Vault 2.0.

McCartney

4:00pm-5:00pm: Designing Big-Data Platforms for an Enterprise

Sridhar Ramaswamy, Ph.D., Digital Analytics Manager, Caterpillar

Big Data analytics is becoming the need of any enterprise. It is primarily driven by two major developments in recent years:

1. Highly-scalable data architecture that enables storage of big data, and
2. Analytics platforms with elastic computing capabilities.

Traditional data processing and analysis of structured data using relational databases or data warehousing no longer satisfy the challenges of big data. Technology trends for big data embrace open source software, commodity servers, and parallely-distributed processing platforms. Analytics is at the core of exploiting values from big data to create consumable insights for businesses. This talk presents the pros and cons of building big data initiatives for an enterprise.

Ramaswamy