The document discusses how data and rigorous hypothesis testing can provide competitive advantages for businesses, both large and small. It advocates developing data strategies and thoughtful data architecture to extract maximum value from data. Founders should focus hypotheses on key business metrics and create a data-driven culture. While not all companies have large datasets, even small data needs management. The proliferation of tools has made advanced infrastructure accessible. Platform businesses should focus first on proving value for a specific use case before pursuing general platform sales.
This framework helps organizations align Data Strategy with Business Strategy to prioritize goals around the most pressing operational needs. It introduces Data Management & Data Ability Maturity Matrix to visualize the core path of business digital transformation, which is easy to understand and follow. And it provides the standard template for implementation, which can share the flexibility to engage applications of different industries.
Presentation: Big Data – From Strategy to Production - Mario Meir-Huber, Big Data Leader Eastern Europe, Teradata GmbH (AT), at the European Data Economy Workshop taking place back to back to SEMANTiCS2015 on 15 September 2015 in Vienna
Talk at IEEE Big Data/Cloud conference in Santa Clara, June 28th, 2013.Jari Koister
Sharing why it is hard to succeed with Big Data/Predictive projects in terms of productionalizing them what you can do to reduce risk while take is steps in the right direction.
This framework helps organizations align Data Strategy with Business Strategy to prioritize goals around the most pressing operational needs. It introduces Data Management & Data Ability Maturity Matrix to visualize the core path of business digital transformation, which is easy to understand and follow. And it provides the standard template for implementation, which can share the flexibility to engage applications of different industries.
Presentation: Big Data – From Strategy to Production - Mario Meir-Huber, Big Data Leader Eastern Europe, Teradata GmbH (AT), at the European Data Economy Workshop taking place back to back to SEMANTiCS2015 on 15 September 2015 in Vienna
Talk at IEEE Big Data/Cloud conference in Santa Clara, June 28th, 2013.Jari Koister
Sharing why it is hard to succeed with Big Data/Predictive projects in terms of productionalizing them what you can do to reduce risk while take is steps in the right direction.
The big data landscape for most enterprises is a vast wilderness. It is a growing and complex ecosystem of different data types from multiple sources, including new data from social media and raw data collected from sources like sensors. Only after effectively exploring and navigating this terrain can businesses begin to mine and refine their data resources to extract value—using trusted information to pave the roads to new insights and smarter decision making.
For more information: www.ibm.com/bigdata
Art by Angela Tuminello
The big data landscape for most enterprises is a vast wilderness. It is a growing and complex ecosystem of different data types from multiple sources, including new data from social media and raw data collected from sources like sensors. Only after effectively exploring and navigating this terrain can businesses begin to mine and refine their data resources to extract value—using trusted information to pave the roads to new insights and smarter decision making.
For more information: www.ibm.com/bigdata
Art by Angela Tuminello
7 Pillars Of Data Strategy - High Five 2018Evan Levy
Data and analytics companies are seemingly everywhere, many claiming to be panaceas for all your data woes. As much as we like to rely on technology, the human factor is still the most important part of the equation. Clear strategy and focused leadership is required to make transformative, meaningful change in data culture, influencing capture, analysis, and presentation of your company’s data.
Big data, your data, all data - Frederik VandeputteInspireX
Big Data, Your Data, All Data, …fast insights through Microsoft BI.
If you take a look at latest Gartner Hype Cycle for Emerging Technologies, you will find Big Data at the peak of inflated expectations. What exactly is Big Data? How can you look at data in a completely different way? How do you exploit the economic value of Big Data, Your Data, All Data … with familiar Microsoft BI tools?
You probably have heard about Big Data, but ever wondered what it exactly is? And why should you care?
Mobile is playing a large part in driving this explosion in data. The data are also created by the apps and other services in the background. As people are moving towards more digital channels, tons of data are being created. This data can be used in a lot of ways for personal and professional use. Big Data and mobile apps are converging in an enterprise and interacting; transforming the whole mobile ecosystem.
Watch Claudia's keynote at Fast Data Strategy Virtual Summit 2018 here: https://buff.ly/2wECySw
The new release of Denodo Platform 7.0 redefines data management for next generation, and propels data-driven business to insights-driven business. Claudia Imhoff is a keynote speaker at the Fast Data Strategy Virtual Summit 2018. Her presentation will focus on data chaos and how companies are dealing with it today because their data is spread across multiple sources and locations. Claudia will speak about solutions that can help organizations bring order to the data chaos and will present the concept of the extended data warehouse architecture and the "brain" needed to make it all work, the data catalog.
Attend this session to discover:
• Perspectives from independent industry analyst Claudia Imhoff
• Why data virtualization is gaining momentum
• How Denodo 7.0 enables next generation data management
What is this ‘Big Data’?
Introduction and Key words
Any secrets behind big data?
The 4V’s of Big Data
Big Data Analytics
What to do with this data?
Usefulness of Business Intelligence (BI)
Data Analytics has become a powerful tool to drive corporates and businesses. check out this 6 Reasons to Use Data Analytics. Visit: https://www.raybiztech.com/blog/data-analytics/6-reasons-to-use-data-analytics
Data-Driven is Passé: Transform Into An Insights-Driven EnterpriseDenodo
Watch the full webinar: http://goo.gl/c5rlCM
Speakers: Holger Kisker, Ph.D., Vice President and Research Director at Forrester Research Inc.
Listen to Holger Kisker, Vice President and Research Director at Forrester Research Inc., describe the three step plan for organizations to become insights-driven rather than data-driven enterprises. Adopting systems of insight and embedding them into your organization’s systems of engagement, record, and automation allows you to turn data into action. As a final step, data virtualization can help keep all systems in synch, being a key enabler for systems of insight.
The big data landscape for most enterprises is a vast wilderness. It is a growing and complex ecosystem of different data types from multiple sources, including new data from social media and raw data collected from sources like sensors. Only after effectively exploring and navigating this terrain can businesses begin to mine and refine their data resources to extract value—using trusted information to pave the roads to new insights and smarter decision making.
For more information: www.ibm.com/bigdata
Art by Angela Tuminello
The big data landscape for most enterprises is a vast wilderness. It is a growing and complex ecosystem of different data types from multiple sources, including new data from social media and raw data collected from sources like sensors. Only after effectively exploring and navigating this terrain can businesses begin to mine and refine their data resources to extract value—using trusted information to pave the roads to new insights and smarter decision making.
For more information: www.ibm.com/bigdata
Art by Angela Tuminello
7 Pillars Of Data Strategy - High Five 2018Evan Levy
Data and analytics companies are seemingly everywhere, many claiming to be panaceas for all your data woes. As much as we like to rely on technology, the human factor is still the most important part of the equation. Clear strategy and focused leadership is required to make transformative, meaningful change in data culture, influencing capture, analysis, and presentation of your company’s data.
Big data, your data, all data - Frederik VandeputteInspireX
Big Data, Your Data, All Data, …fast insights through Microsoft BI.
If you take a look at latest Gartner Hype Cycle for Emerging Technologies, you will find Big Data at the peak of inflated expectations. What exactly is Big Data? How can you look at data in a completely different way? How do you exploit the economic value of Big Data, Your Data, All Data … with familiar Microsoft BI tools?
You probably have heard about Big Data, but ever wondered what it exactly is? And why should you care?
Mobile is playing a large part in driving this explosion in data. The data are also created by the apps and other services in the background. As people are moving towards more digital channels, tons of data are being created. This data can be used in a lot of ways for personal and professional use. Big Data and mobile apps are converging in an enterprise and interacting; transforming the whole mobile ecosystem.
Watch Claudia's keynote at Fast Data Strategy Virtual Summit 2018 here: https://buff.ly/2wECySw
The new release of Denodo Platform 7.0 redefines data management for next generation, and propels data-driven business to insights-driven business. Claudia Imhoff is a keynote speaker at the Fast Data Strategy Virtual Summit 2018. Her presentation will focus on data chaos and how companies are dealing with it today because their data is spread across multiple sources and locations. Claudia will speak about solutions that can help organizations bring order to the data chaos and will present the concept of the extended data warehouse architecture and the "brain" needed to make it all work, the data catalog.
Attend this session to discover:
• Perspectives from independent industry analyst Claudia Imhoff
• Why data virtualization is gaining momentum
• How Denodo 7.0 enables next generation data management
What is this ‘Big Data’?
Introduction and Key words
Any secrets behind big data?
The 4V’s of Big Data
Big Data Analytics
What to do with this data?
Usefulness of Business Intelligence (BI)
Data Analytics has become a powerful tool to drive corporates and businesses. check out this 6 Reasons to Use Data Analytics. Visit: https://www.raybiztech.com/blog/data-analytics/6-reasons-to-use-data-analytics
Data-Driven is Passé: Transform Into An Insights-Driven EnterpriseDenodo
Watch the full webinar: http://goo.gl/c5rlCM
Speakers: Holger Kisker, Ph.D., Vice President and Research Director at Forrester Research Inc.
Listen to Holger Kisker, Vice President and Research Director at Forrester Research Inc., describe the three step plan for organizations to become insights-driven rather than data-driven enterprises. Adopting systems of insight and embedding them into your organization’s systems of engagement, record, and automation allows you to turn data into action. As a final step, data virtualization can help keep all systems in synch, being a key enabler for systems of insight.
Copy of presentation delivered at the CHASS 2015 National Forum in Melbourne (October 2015), The Council for Humanities, Arts and Social Sciences in Australia is the peak body supporting more than 75 member organisations in their relationships with Federal and State Government policy makers, Academia and the broader community within Australia.
Bardess Moderated - Analytics and Business Intelligence - Society of Informat...bardessweb
Joe DeSiena, President of Bardess Group Ltd moderated a panel of Information Technology executives titled Analytics and Business Intelligence for the chapter meeting for the New Jersey Society of Information Management.
The customer journey could essentially be divided into 7 elements. We’ll touch upon the issue of ‘Privacy’ and how one balance social and commercial value. Practical examples of
customer analytics at its best will be discussed as well as the importance of the eco-system.
Big data + data science startup focus pointsTom Zorde
Use these slides to the focus conversation and evaluate a big data/data science start-up idea. Enjoy :)
What stage are you at?
What is the problem you’re trying to solve?
What type of business model would work?
Tools? – A rapidly evolving space.
Reference Architecture helps identify what level of the stack we’re talking about.
Twitter: @TomZorde
Twitter: @TomZorde
Web: http://www.zorde.com
LinkedIn: http://linkedin.com/in/zorde
Data Strategy - Executive MBA Class, IE Business SchoolGam Dias
For today's enterprise Data is now very much a corporate asset, vital to delivering products and services efficiently and cost effectively. There are few organizations that can survive without harnessing data in some way.
Viewed as a strategic asset, data can be a source of new internal efficiencies, improved competitive advantage or a source of entirely new products that can be targeted at your existing or new customers.
This slide deck contains the highlights of a one day course on Data Strategy taught as part of the Executive MBA Program at IE Business School in Madrid.
How to Create More Effective Storytelling by Leveraging DataCourse5i
Today, dashboards have become the epitome for communicating important business data and performance metrics. Instrumental in helping organizations achieve corporate alignment around business goals and objectives, they enable faster decision making, drive data-driven business strategies and ensure ROI.
Yet, the road to building dashboards for effective storytelling is not always easy. Often organizations struggle to create the right visual dashboards due to missing links between the data and story, or the amount of time and budget invested, which digress from the main objective of the visualization exercise. Additionally, the approach to storyboard development has been traditionally flawed with just a focus on the analysis – not telling a broader story. Then, even after organizations fine tune their dashboard and align with corporate objectives, they can still find themselves falling down in terms of adoption.
In this webinar, Anees Merchant, Senior Vice President of Blueocean Market Intelligence, will share with attendees how to develop a strong practice around data visualization and structure effective processes for success. Anees will also share various best practices and mistakes to avoid so organizations can produce powerful, actionable dashboards that are intuitive and include insights that are easily interpreted by all stakeholders.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Five Attributes to a Successful Big Data StrategyPerficient, Inc.
The veracity, variety and sheer volume of data is increasing exponentially. With Hadoop and NoSQL solutions becoming commonplace, there are many technical options for managing and extracting value from this data. Many companies create labs to experiment with Big Data solutions, only later become IT playgrounds or unstructured dumping grounds.
To help avoid these pitfalls,companies with successful Big Data projects approach challenges by formulating a strategy that assures real business value is derived from their Big Data investments. In a Perficient poll, 73% of companies stated they are in the early-evaluation stage to find solutions to their Big Data problems and are only beginning to create their strategy.
Join us for a webinar featuring thought-provoking best practices used by successful companies to quickly realize business value from their Big Data investments. You'll learn:
The top five steps to increased business value
What the top companies are doing in Big Data that you need to know
Next steps to lay the ground work for a successful Big Data strategy
How the Analytics Translator can make your organisation more AI drivenSteven Nooijen
Today, about 80% of companies considers data as an essential part of their strategy. However, although most of these companies are taking models into production, they still have trouble turning their data and insights into valuable AI solutions. With businesses heavily invested in data and AI, what is it that actually makes the difference for being successful with AI?
In this talk, I will argue that the extent to which AI is embedded in the organisation is crucial to success. Furthermore, I will show why the Analytics Translator is the designated person to drive AI adoption by the business and what his or her tasks should look like. The insights shared come from our own experience as consultants as well as interviews with top Dutch enterprises about their AI maturity.
AI Maturity Levels and the Analytics TranslatorGoDataDriven
Buzzwords like Big Data, Cloud, and AI have been out there now for a couple of years. But today, businesses have a clear focus on the application of data use cases and the challenges around that such as metadata management, governance, security, and maintainability in general. Everybody seems to have some version of a data lake and wants to consolidate it into something (more) useful, or move from an on-premise version to the cloud. There is a general need to streamline current practices while also attempting to give multiple segments of users (data scientists, analysts, marketeers, business people, and HR) access in a way that is tailored to their needs and skills. In other words: businesses today are heavily invested in data and AI, but many have a hard time knowing how to mature it to the next level.
This is exactly where a "maturity model" comes into play. The goal of a maturity model is to help businesses in understanding their current and target competencies. This helps organisations in defining a roadmap for improving their competency. A maturity model is therefore one way of structuring progression, whether the company already embraces data science as a core competency, or, if it is just getting started.
In this presentation on maturity models, we answer the following questions:
1. What exactly is a maturity model and why would you need it? We address this by sharing GoDataDriven's maturity model and describing the different phases we have identified based on our experience in the field.
2. How can you use a maturity model to advance your organisation? Having a maturity model alone is not enough, in order for it to be valuable you need to act upon it. This paper provides concrete examples on how to do act based on practical stories and experiences from our clients and ourselves.
Altis Webinar: Use Cases For The Modern Data PlatformAltis Consulting
Several organisations have mentioned issues that they have found from choosing the wrong use cases to start their journey with a modern data platform.
In this session, NZ Regional Manager Alex Gray will cover some of those issues faced by organisations & how to pick the right use cases to get you started successfully on your journey.
Are you getting the most out of your data?SAS Canada
Data is an organizations most valuable asset, but raw data by itself has little value. To drive data’s worth, it must be managed and processed to extract value and information that decision makers can leverage and turn into actionable insights. It is the ways in which a company choses to put that information to use that will determine the true value of its data.
Through business intelligence and business analytic tools, businesses are enabling themselves to make more strategic, accurate decisions, while optimizing business processes. Hear from Info-Tech Research Group and learn what you need to consider when choosing an analytics solution provider. The webinar will highlight Info-Tech Research Group’s recently published vendor landscape for selecting and implementing Business Intelligence and Business Analytics solutions. The report positions SAS as the only leader across all four categories of Enterprise BI, Mid-Market BI, Enterprise BA and Mid-Market BA.
This is the deck from the Big Data and Social Insights breakout session from the Becoming a Customer Company event on July 17th, 2013. For more information, please head to magnet360.com
Ana Villegas, Dell - Using Data, Technology and Creativity to Break Through T...Marketing United
Digital marketing is a crucial part of any B2B marketing strategy. Today, B2B marketers are faced with the challenge of breaking through the noise and using programmatic to optimize both content and marketing strategies to reach BDMs and ITDMs. Using cutting edge data technology to fuel unique and creative strategies, Dell is going beyond Digital 101 to become a thought leader in the world of digital B2B marketing.
Similar to The Research Board Presentation (1) (1) (20)
2. Confidential and Proprietary - Not for Distribution 2
Background
• Managing Partner of IA Ventures, a $155M venture firm
focused on creating competitive advantage through data
o Lead-managed companies include Datasift, Digital
Ocean, MemSQL, Simple and Transferwise
• 5 years as a professional angel investor
o Early investor in Buddy Media (SalesForce), Invite Media
(Google), Magnetic, TubeMogul (IPO) and TweetDeck
(Twitter)
• 18 years on Wall Street (Citi, Deutsche) in Capital
Structuring, Derivatives and Quantitative Trading
3. • The key to unlocking data’s value is through rigorous
hypothesis development and testing
• But before you can ask questions, the data needs to be
in the right form
• Data Strategy = Business Strategy
• These principles apply not only to startups but multi-
nationals as well
Confidential and Proprietary - Not for Distribution 3
Beyond Buzzwords
4. Data is:
● Easier to access (proliferation of APIs)
● Cheap(er) to process and store (cloud)
● The beneficiary of better tools for
business analysis (DSaaS)
● More easily actionable in (near) real-
time (feedback loops, machine learning)
Confidential and Proprietary - Not for Distribution 4
Evolution of the Data-Driven Business
5. ● The best founders think deeply about what they are
trying to prove, and tie these hypotheses to core
business metrics
● This creates a data-driven culture that fuels critical
insights and permeates everything they do
● This extends into how they think about their natural
data assets as well as the metadata that can be
extracted for important business decisions
● This requires coordination among and commitment
from many constituencies across the organization:
Operations; Development; Product; Sales; and Senior
leadership
Confidential and Proprietary - Not for Distribution 5
Hypothesis Development
6. ● Virtually every startup (and every company) has data
as a key strategic asset
● While not all businesses have streaming data-at-scale,
even “small data” needs to be managed well for
extracting maximum value
● Thoughtful architecting of the data environment
upfront can save huge amounts of pain further down
the road
● The proliferation of low-cost on-demand tools has
brought institutional-grade infrastructure within reach
of the small enterprise
Confidential and Proprietary - Not for Distribution 6
Data Enablement
7. ● Almost all of the businesses we invest in are building
“platforms”
● Founders almost always focus on a single high-value
use case to prove the value of the platform: general
platform sales are “out”, while specific product sales
are “in”
● Refining the first product to ensure tight
product/market which demonstrates the power of the
platform is key
● Creating matrix organizations that support investment
in both the platform and the products is essential for
innovation - and survival
Confidential and Proprietary - Not for Distribution 7
Platforms for Profit
8. ● What are some new opportunities for
data-driven business models?
● How can data be used to drive
competitive advantage?
● Can data be used to secure barriers to
entry?
Confidential and Proprietary - Not for Distribution 8
The Big Questions
9. ● 2-sided markets (CareGuardian,
NewsCred)
● Contributory databases (BillGuard,
Metamarkets)
● Turning 3rd party data into 1st party
data (The Trade Desk, Transferwise)
EACH OPPORTUNITY LEVERAGES DATA FOR COMPETITIVE
ADVANTAGE AND CREATES BARRIERS TO ENTRY
Confidential and Proprietary - Not for Distribution 9
New Opportunities for Leveraging Data