Bio: Bob Baran, is a Senior Field Engineer for the East, brings more than 25 years of database experience to the Splice Machine team. Previously, Bob was a Senior Field
Engineer at ParAccel which was a columnar MPP analytic database. Prior to ParAccel,
Bob was a Solution Architect at Teradata, spent 20 years at IBM and was a database developer at AT&T.
Abstract: Managing Big Data: Scaling Options
In this presentation, we will discuss scaling choices to Big Data, your options, decision points, and how to use existing infrastructure. Traditional relational databases like Oracle and IBM have been the de facto RDBMSs for decades. They do many things very well and are still a strong choice for high performance transactional systems, especially for data volumes below a few terabytes. However, when data volumes begin to scale, many enterprises are looking for more cost-effective alternatives.
Distributed computing (i.e., the ability to scale out on commodity hardware) is a disruptive technology underpinning the new wave of database innovators such as
SQL-on-Hadoop, NoSQL and NewSQL solutions. These solutions can offer a dramatic price/performance improvement over legacy databases. Incumbent database vendors have faced threats to their dominance in the past, but it is different this time, because of the volume, velocity, and variety of data growth.
In this presentation we will cover an overview of the Big Data landscape with a focus on scale out architectures.
Bio: Rob Loranger is an Embarcadero Product Manager for the ER/Studio product family. Previous to his current role, Rob was a Sr. Software Consultant, and for more than 8 years he has been one of Embarcadero's leading experts for its database development, management, and architecture software.
Abstract: Best Practices for Mapping your Master Data Landscape
Similar to all data, master data has little value to an organization if the organization doesn’t know where the data lives, how to interpret it, and who stewards over it.
However, the difference is that the stakes of not knowing the answers to these questions are much higher for master data than they are for transactional or reference data. As an example, product data in a manufacturing business is used in many areas such as bill of materials, inventory configurations, and parts specifications. Among the problems that can occur, if the correct product data is not used in these areas, the cost of a product can be drastically miss calculated and its quality can be severely degraded. Metadata is essential to avoid these consequences. In this session, we’ll discuss best practices for using data models to capture essential metadata and to map your master data landscape.

Bio : David Loshin , president of Knowledge Integrity, Inc, ( www.knowledgeintegrity.com
), is a recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master data management, and business intelligence. Along with consulting on numerous data management projects over the past 15 years, David is also a prolific author regarding business intelligence best practices, as the author of numerous books and papers on data management, including the recently published “Big Data Analytics: From Strategic Planning to
Enterprise Integration with Tools, Techniques, NoSQL, and Graph,” the second edition of “Business Intelligence – The Savvy Manager’s Guide,” as well as other books and articles on data quality, master data management, big data, and data governance. David is a frequent invited speaker at conferences, web seminars, and sponsored web sites and channels including www.b-eye-network.com
, and share additional content at his notes and articles at www.dataqualitybook.com
David can be reached at loshin@knowledge-integrity.com
, or at (301) 754-6350. Knowledge
Integrity Incorporated Business Intelligence Solutions
Abstract: An Engagement Model for Master Data Management Consumers
Too often a master data management capability has been designed, developed, and deployed with an overwhelming focus on data ingestion and integration. However, when the opportunities arise for making use of the master data environment, the absence of process and services for publication or syndication of managed master data makes it difficult, if not improbable that a consuming application can easily adopt the use of the MDM system.
The objective of the Engagement Model is to streamline the process for business process owners interested in using MDM services to integrate their processes and applications with the MDM services stack. The MDM Engagement Model describes the steps for analyzing and documenting requirements and then developing a roadmap and plan for providing or using master data such as:

Supplying source data about entities;

Resolving the identities of the entities represented in data sets;

Providing a searchable and JOINable index of entity data;

Establishing connections among source data records associated with uniquely identified entities; or

Enabling access to entity data for analytical purposes.
In this talk we will explore the development of an MDM Engagement Model to help guide business process owners in developing the project plan for consuming applications to integrate the use of master data. At the same time, for suppliers of master data, the Engagement Model will frame the development of Interface Control
Documents and other documents guiding integration. Attendees will learn about:

Common MDM use case scenarios;

Master data events;

Master data services;

Understanding MDM performance expectations;

Organizational preparedness for embracing MDM.

Bio: David Majcher , IBM Information Architect
David has been with IBM for 14 years as a subject matter expert in Data governance,
Information Management, Data Life Cycle Management, Data Warehouse, Database and Analytics. He is the president of the local TDWI Chicago Chapter and lead for the Chicago DB2 Midwest users group. Dave has presented at hundreds of customers,
IDUG, IBM and Data Governance conference in France. Before IBM, he was a system DBA for DB2 z/OS, IDMS, an application DBA for DB2, Teradata, Oracle,
Informix and UNIX administrator along with owning his own consulting practice.
Abstract: Looking at Hadoop “Big Data” in the rearview mirror
What would you have done differently after implementing a data lake? Come join
David Majcher, IBM Information Architect, discussing the ins and outs of implementing a data lake along with best practices. A breakout session will follow discussing different implementation strategies focusing on technical and business drivers.
Bio: Robert S. Seiner is a n industry leader in the field of data governance, data stewardship and meta-data solutions specializing in Non-Invasive Data
Governance™. Mr. Seiner is the President and Principal Consultant of KIK
Consulting & Educational Services - http://www.KIKconsulting.com
(Knowledge is
King) and he is the Publisher of The Data Administration Newsletter at www.TDAN.com
. Mr. Seiner’s first book Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success (Technics Publications) was published in
September . Mr. Seiner was recognized with the DAMA International Professional
Award for his significant, demonstrable contributions to Information resource management and data resource management. Mr. Seiner can be reached at rseiner@tdan.com
or 412.220.9643.
Abstract: Formalization of Data Stewardship to Succeed in Data Governance
The governance of data is already taking place in your organization. The same thing can be said for the stewardship of data – albeit in a mostly informal, inefficient and ineffective manner. Non-Invasive Data Governance focuses on the formalization of accountability and the application of governance to existing and / or new processes as a less threatening approach. In this session Bob Seiner will share his “everybody is a data steward” concept and how it may be the key to program success. Bob will talk about how to formalize existing levels data governance and data stewardship as a way to start a new program and how to benefit from this concept to enhance an existing program. The topics he will address include:

Concepts of a Non-Threatening Approach

8 Rules for Becoming a Data Steward

Different Levels of Stewards

Formalizing Governance Through Process
 The Data Governance Bill of “Rights”

Bio: Alan White has a 20+ year track record as an entrepreneur and managing consultant including acting/interim CEO, CIO and CFO positions. Alan has demonstrated pragmatic leadership and innovation in Information Technology with primary focus on Information and Data Management, Data Governance and Analytical
Systems. Mr. White has led senior teams developing solutions supporting business needs in the areas of Risk, Compliance, Regulatory and Governance on Operational,
Tactical and Strategic initiatives.
He serves on the board of Zoeal LLC, is Advisor to IT Consulting, Inc. (a company he founded in 1994), KidBacker.com and Smartzer.com (a company he Angel Funded).
He has previously founded three companies focused on supplying information technology to fill marketplace gaps; addressing Deep Web Technology for Real Estate
(2005), Data Profiling (1999) and an Online Bookstore (1995).
Abstract: Information Orchestration in the Modern Data Jungle
As business becomes more complex with Omni-Channel marketing, many and varied prospect and customer touch points, product/brand complexity and sometimes regulatory, risk and compliance considerations how is an enterprise to (survive first) and, furthermore, liberate data to become usable information?
In addition, technology advancements such as wearable fashion, IoT (Internet of
Things), social media channels and third party solutions further extend the size, complexity and variety of the technology ecosystem. Additional considerations such as function to technology fit, hybrid data environments, legacy/NewDB Structures and non-standard data definitions add angst to the modern data governance challenge.
This session will present case studies and pragmatic approaches to steward data from a business focused lens to encourage a sustainable Enterprise Information Strategy.
It’s a jungle out there.