The Agile Analyst: Solving the Data Problem with Virtualization

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The Briefing Room

The Agile Analyst: Solving the Data Problem with Virtualization

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Welcome

Host: Eric Kavanagh

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Mission


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Topics

This Month: ANALYTICS

February: BIG DATA

March: CLOUD

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room


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Analytics

You want your analyst to look like THIS

NOT like THIS


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Analysts: Lindy Ryan and John O’Brien

Lindy Ryan is the Research Director for Radiant Advisor’s Data Discovery and Visualization practice and leads research and analyst activities in the confluence of data discovery, visualization, and data science from a business needs perspective. She also retains the role of Editor in Chief of RediscoveringBI Magazine. As Radiant Advisors’ Editor in Chief for three years, Lindy participated in in-depth discussions and analysis with industry thought leaders and vendors while maturing her position and perspectives in the BI industry.

John O’Brien is Principal and CEO of Radiant Advisors. With over 25 years of experience delivering value through data warehousing and BI programs, John’s unique perspective comes from the combination of his roles as a practitioner, consultant, and vendor in the BI industry. His knowledge in designing, building, and growing enterprise BI systems and teams brings real world insights to each role and phase within a BI program. Today, through Radiant Advisors John provides research and advisory services that guide companies in meeting the demands of next generation information management, architecture, and emerging technologies.


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Cisco

!   Cisco Systems is a known leader in the design, manufacturing and sales of networking equipment

!   Through its acquisition of Composite Software, Cisco is expanding its footprint in the Data Virtualization space

!   Cisco will soon announce Data Collage, a new product designed to quickly gather and integrate data from enterprise sources


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Guest: Marc Breissinger

Marc Breissinger joined Cisco Systems during its 2013 acquisition of Composite Software. As Director of Advanced Services for the Cisco Data Virtualization Business Unit, he advises Fortune 500 clients on advanced data virtualization strategies, architectures, and implementations, having. As CTO of webMethods, he guided internal and key account technology strategy and architecture. Marc’s efforts resulted in millions in new revenue, multiple new products and seven acquisitions. Prior to webMethods, Marc was a Senior Manager at Andersen Consulting (now Accenture) where he successfully led over a dozen major projects in Automotive, Electronics, Chemical and Retail market clients.

© 2013 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 10 © 2013 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 10

Solving the Data Problem with Virtualization

Bloor Group Briefing Room

January 2014

© 2013 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 11

Find the Data

Access the

Data

Build a Sandbox

for the Data

Build the Model

Analyze the

Results

Develop the

Business Insight

Analysts spend more than half their time

pulling together their data


§  Data is increasingly distributed and heterogeneous

§  Demand for short lived analytics in increasing

§  It is unrealistic to expect IT to consolidate/generate datasets on demand

Third Party Data

Analytic Stores & Sandboxes

Transactional & Operational Stores

Data Warehouses & Marts

Enterprise Applications

SaaS Applications

“Big” Data & NoSQL

Personal & Departmental


Cisco Collage lets analysts quickly pull together all the data they need without all the hassle. Unlike traditional sandbox building approaches that are cumbersome or highly dependent on IT, Cisco Collage brings elegance and productivity to the task of gathering and staging data. Analysts now have more time to actually analyze the data within their favorite front-end analytic tool.


Analytic DI Agility with Self-Service

Capabilities •  Install on your desktop quickly •  Access data from anywhere •  Browse through data efficiently •  Combine data easily •  Transform/enrich data •  Accessible from any analytic app •  Share data with teammates

Benefits •  Spend more time

analyzing data •  Less time gathering data •  Greater overall

productivity






SaaS Applications

Third Party Data

Visualization Power Analytics/Mining Traditional BI


How it works






SaaS Applications

Third Party Data

Visualization Power Analytics/Mining Traditional BI

Data Collage Application/Service Personal Sources

xlsx mdb

csv

MySql External

Local Materialization (Optional)


Fits into the way you do things

Increased Agility

Self Service

Collaboration •  Sandboxes can be

shared, changed, and reused

•  IT can easily incorporate your work into enterprise systems

•  Access the information you need without delay

•  Reduce your dependence on IT to create complex data environments

•  Respond quickly to changing business needs

•  Bring data together from any data source at run time

•  Sandboxes make your queries run faster

•  No need to learn another reporting or analytics tool

•  Fits into the full data analysis life cycle


TOMORROW starts here.


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Perceptions & Questions

Analysts: Lindy Ryan and John O’Brien

© Copyright 2014 Radiant Advisors. All Rights Reserved v1.10.000

ENABLING THE AGILE ANALYST

19

Inside Analysis – The Briefing Room with Cisco – January 21, 2013

Lindy Ryan | Research Director, Data Discovery & Visualization

@lindy_ryan [email protected]

John O’Brien | Principal Analyst, Modern Data Platforms @obrienjw [email protected]


CHALLENGES IN DATA DISCOVERY Enabling the Agile Analyst

20

Business knowledge required •  Business analysts and intuitive tools

•  Iterative process to explore and “fail fast”

•  Data doesn’t integrate easily or data quality

Data is everywhere •  Data warehouses contain predefined data •  Other operational data •  Personal or local data •  External or big data


THE NEW MODERN ANALYST Enabling the Agile Analyst

21

Empowering users with data is to enable data discovery, and redefining the modern business analysts to do more

More complete self-sufficiency to work with data in their own way and speed

Not just self-service access to data but data acquisition, integration and analytics

Reshaping the role of traditional IT to ET: Enablement Technology

Download Insight Paper: From Self-Service to Self-Sufficiency --- How Discovery is Driving the Business Shift


DATA VIRTUALIZATION IS AGILITY Enabling the Agile Analyst

22

Data abstraction and federation is the key to enabling agility and self-sufficiency in working with data

Reduces the need for support to move and re-store data for analysis and exploration

Views represent integrations that are meta data and easily re-mapped

A technology/tool that specializes in accessing all forms of data and services


INFORMATION LIFE CYCLES Enabling the Agile Analyst

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Other considerations with Discovery as a process •  Life after discovered context

•  Collaboration in discovery but not in definition

•  Governance process for definitions

•  Local Discovery, Team Collaboration, Enterprise Context

•  Moving virtualized data from personal to enterprise process

Where: consider the migration of data integrations from personal environments to departmental or enterprise. This still involves enterprise data virtualization servers.

1

Information lifecycle and governance required to verify and determine where integrations should reside in the information architecture as materialized or virtualized

How: consider processes that are self-regulating, such as peer reviews and collaboration for context and analytics. Work with IT and BI teams for performance requirements for long-term.

2


THANK YOU!

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Email: [email protected]

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www.radiantadvisors.com/rediscoveringbi

24


Inside Analysis | Cisco Briefing Room 1/21/2014 ANALYST QUESTIONS

1.  Is discovery the primary application of Cisco Collage?

2.  Is discovery part of the information lifecycle, i.e., are integrations migrated to enterprise or production?

3.  Discuss the relationship with analytic sandboxes.

4.  Are data definitions in Collage collaborative? Can users access other analyst’s data?

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This Month: ANALYTICS

February: BIG DATA

March: CLOUD


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