HOW TO BECOME DATA DRIVEN (PANEL) - ALPESH DOSHI

•

0 likes•142 views

Co-founder of Fintricity, the company specialized in helping enterprises leverage big data and analytics solutions, technology and cloud. Fintricity also works in Digital Transformation and its application within companies to transform how they become a 21st century company.

Technology

Title: How to Become Data Driven
Moderator: Alpesh Doshi, Fintricity
Panelists
• Jim Annning, British Gas, Connected Homes
• Kriti Sharma, Barclaycard
• Matthew Doubleday, Shopdirect

How to Become Data Driven: Questions
What are the key parts of your business that you see
that Data plays a crucial part?
Are there any types of data you see that are crucial to
collect, organise and use?
Do you anticipate any issues with using the data that
is collected?

How to Become Data Driven: Questions
What are the key aspects of your business that you
see can make you data driven?
Are there data privacy and governance concerns
processes and procedures that you’ve established?
What’s the future of how you can transform your
business to become data driven.

Title: Open Sans 100 px
• Subtitle: Open Sans 48 px

Similar to HOW TO BECOME DATA DRIVEN (PANEL) - ALPESH DOSHI

The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Governance Strategies

Data Blueprint

The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Takeaways: Understanding why data governance can be tricky for most organizations Steps for improving data governance within your organization Guiding principles & lessons learned Understanding foundational data governance concepts based on the DAMA DMBOK

Data-Ed Online Webinar: Data Governance Strategies

DATAVERSITY

In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change. Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.

The Business Value of Metadata for Data Governance

Roland Bullivant

Data is everywhere in today’s businesses, and there are countless things for the data professional to do! It can be overwhelming to figure out what we should be doing now, tomorrow, and further down the road. Data Leadership helps us simplify, prioritize, and ultimately find the direction we need. The value that comes from data can impact an organization in three fundamental ways: increasing revenues, decreasing costs, and managing risk. Data professionals are tasked to optimize data’s impact on these. But knowing our goals—versus how to best achieve them—are two very different things. The Data Leadership Framework guides us in sorting out the dozens of choices to determine the best actions to take, no matter where we are in our data journey. Attend this DATAVERSITY webinar to start maximizing data value with Data Leadership!

Webinar: Maximizing Your Potential with Data Leadership

DATAVERSITY

Big Data Panel

AMA Iowa (American Marketing Association Iowa Chapter)

A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age A Basic Review of BI and DM How to Implement BI A review of BI Tools and 2022 Gartner Quadrant Magic Basics of Data warehouse (DWH) An introductions to Power BI Components of Power BI Steps for BI Implementation Data Culture Intro to ETL and ELT OLAP files and Architecture Digital transformation or DX review A glance at DMBOK2.0 framework BI Challenges Data Governance Data Integration Data Security and Privacy in DMBOK2.0 Data-Driven Organization Data and BI Maturity Model Traditional BI Self-service BI who is DMP who is BI developer what is Metadata what is Master data Data Quality Data Literacy Benefits of BI BI features How does BI Works? Modern BI Data Analytics BI Architecture Data Types Data Lake Data Mart Data Silo Data Visualization Power BI Architecture and components

Business Intelligence (BI) and Data Management Basics

amorshed

At its core, Data Governance (DG) is: managing data with guidance. This immediately provokes the question: Would you tolerate your data managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides your organization with an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a necessary prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Program learning objectives include: • Understanding why Data Governance can be tricky for organizations due to data’s confounding characteristics • Strategy No. 1: Keeping DG practically focused • Strategy No. 2: DG must exist at the same level as HR • Strategy No. 3: Gradually add ingredients • Data Governance in action: storytelling

DataEd Slides: Approaching Data Governance Strategically

DATAVERSITY

The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Takeaways: Understanding why data governance can be tricky for most organizations Steps for improving data governance within your organization Guiding principles & lessons learned Understanding foundational data governance concepts based on the DAMA DMBOK

Data-Ed Webinar: Data Governance Strategies

DATAVERSITY

The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Governance Strategies

Data Blueprint

For any organization to be successful, whatever we do with data must connect to meaningful business improvements—and those must be measured. If current data efforts lack results or accountability, then Data Leadership is our answer.   But Data Leadership isn’t really about the data at all. What makes Data Leadership so powerful is its ability to completely transform organizations. Going beyond traditional data management and governance, Data Leadership builds momentum and delivers the change we’ve long known our businesses need. Data Leadership helps us overcome the lingering data challenges our legacy approaches never will.   This webinar will cover the key concepts of Data Leadership, and what anybody can do to start making a bigger impact for their teams and businesses. Whether your role today is large or small, Data Leadership will be essential to your future data success!   Key Learnings Include:   <ul><li>What Data Value really is, and why creating it is the goal of everything we do with data</li><li>Introduction to the Data Leadership Framework</li><li>Why Data Leadership is fundamentally about balance</li><li>How to immediately start making a Data Leadership impact in your organization</li></ul>

Data Leadership - Stop Talking About Data and Start Making an Impact!

DATAVERSITY

So many companies and organizations are in the same boat. They’re drowning in their data — so much data, from so many different sources. They understand that data governance is hugely important for them to be able to know their data inside and out and comply with regulations. What many companies have not yet come to terms with when implementing their data governance strategy and supporting tools, is the criticality of metadata in the process. As the ‘data about data,’ metadata provides the value and purpose of the data content, thereby becoming an extremely effective tool for quickly locating information – a must for BI groups dealing with analytics and business user reporting. Octopai's CEO, Amnon Drori will discuss this critical missing link in enterprise data governance and the impact of automating metadata management for data discovery and data lineage for BI. He'll demonstrate how BI groups use Octopai to not only locate their data instantly, but to quickly and accurately visualize and understand the entire data journey to enable the business to move forward.

The Missing Link in Enterprise Data Governance - Automated Metadata Management

DATAVERSITY

Metadata management is critical for organizations looking to understand the context, definition and lineage of key data assets. Data models play a key role in metadata management, as many of the key structural and business definitions are stored within the models themselves. Can data models replace traditional metadata solutions? Or should they integrate with larger metadata management tools & initiatives? Join this webinar to discuss opportunities and challenges around: How data modeling fits within a larger metadata management landscape When can data modeling provide “just enough” metadata management Key data modeling artifacts for metadata Organization, Roles & Implementation Considerations

Data Modeling & Metadata Management

DATAVERSITY

ACEDS-Zylab 4-3-15 Webcast

Logikcull.com

Cff 2014 data gov session

Beth Fitzpatrick

Many companies had to roll out MS Teams over the last few months in a hurry with little to no time to think about governance and no budget for adoption & change activities. Realization set in later that giving the business users everything was not the best option. Topics like naming conventions, when to use which tool, team creation, external users, mobile device management, and more need to be addressed after all. Join this session to learn how to reign in an ad hoc MS Teams rollout that will make the IT team sleep better at night, the business users feel less overwhelmed, and create sustainability. Or join this session to learn how to plan your upcoming roll out thoroughly to make it a success for everyone during these difficult times. Antje Lamartine & Thomas Gölles

Scottish Summit 2021 The Myth of a successful Teams rollout

Thomas Gölles

Anyone that works with data downstream in an organization has seen things go...wrong, while upstream managers and business leaders are being held accountable. Whether it's a failure in process, or something technically goes wrong, working with data is not always easy. What happened? How can we prevent it from happening again? What's next? This talk, given at the Portland Data Science Group on October 27, 2016, uncovers 4 common foibles of working with organizational data.

Four Short Foibles of Organizational Data

Lars von Sneidern

Accenture Big Data Expo

BigDataExpo

Basics of BI and Data Management (Summary).pdf

amorshed

Enterprise social networks require governance to operate most effectively, especially in highly regulated industries. It's a slippery slope - the more restrictive your governance policies, the less likely you are to see users collaborating naturally and often. Plus, when you’re used to thinking of “governance” in a SharePoint context, it can be difficult to understand how to govern a Yammer network properly while still encouraging user engagement. When embracing enterprise social, it's important to understand the differences between social collaboration and the collaboration characteristics of older, document-first systems. In this session, we covered: -Best practices for governing a Yammer network -The philosophical differences of governance in SharePoint and Yammer, and why sometimes less is more -The features and functions that Yammer provides for governing users and content

Planning for Governance in Yammer While Working Like a Network

Perficient, Inc.

Big Data - Bridging Technology and Humans

Mark Laurance

Similar to HOW TO BECOME DATA DRIVEN (PANEL) - ALPESH DOSHI (20)

Data-Ed: Data Governance Strategies

Data-Ed Online Webinar: Data Governance Strategies

The Business Value of Metadata for Data Governance

Webinar: Maximizing Your Potential with Data Leadership

Big Data Panel

Business Intelligence (BI) and Data Management Basics

DataEd Slides: Approaching Data Governance Strategically

Data-Ed Webinar: Data Governance Strategies

Data-Ed: Data Governance Strategies

Data Leadership - Stop Talking About Data and Start Making an Impact!

The Missing Link in Enterprise Data Governance - Automated Metadata Management

Data Modeling & Metadata Management

ACEDS-Zylab 4-3-15 Webcast

Cff 2014 data gov session

Scottish Summit 2021 The Myth of a successful Teams rollout

Four Short Foibles of Organizational Data

Accenture Big Data Expo

Basics of BI and Data Management (Summary).pdf

Planning for Governance in Yammer While Working Like a Network

Big Data - Bridging Technology and Humans

More from Big Data Week

BDW17 London - Edward Kibardin - Mitie PLC - Learning and Topological Data A...

Big Data Week

BDWW17 London - Steve Bradbury, GRSC - Big Data to the Rescue: A Fraud Case S...

Big Data Week

Ten years ago there were rumours of the death of causal inference. Big data was supposed to enable us to rely on purely correlational data to predict and control the world. In this talk, I argue that the rumours were strongly exaggerated. Causal inference is becoming increasingly relevant thanks to improvements in inference methods and–ironically–the availability of data. Far from becoming marginalised, causal inference is today more relevant than it’s ever been.

BDW17 London - Totte Harinen, Uber - Why Big Data Didn’t End Causal Inference

Big Data Week

As far as data is concerned, Pharmaceutical Companies have always been clear-sighted and assertive on what insights to get from it, how, and what to do about it. And then the Big Data Era came in, with its frantic pace, transforming multiple industries all around but, for a number of reasons (privacy and data protection issues on top but not alone) keeping the Pharma Industry behind. How to run the extra mile to keep up with the powerful changes Big Data brings along has become a major concern. Strategic opportunities seem to be around the corner. Is the time to bridge gaps finally here?

BDW17 London - Rita Simoes, Boehringer Ingelheim - Big Data in Pharma: Sittin...

Big Data Week

Hello London, the ground-breaking media partnership between Transport for London (TfL) and Exterion Media, gives new opportunities for brands to talk to the London audience in innovative ways and generates vital revenue for London’s transport network. TfL and Exterion have been working together in the Hello London partnership for a year. Part of the collaboration was around the utilisation of data collected by TfL to better inform advertising investment decisions. This has led to ground-breaking work in the Out-of-Home advertising sector and the first example of this is Taps Segmentation. Developed by the TfL Data Science team, it allows Exterion to understand demographic patterns at stations based on aggregated contactless and Oyster card usage. This de-personalised data can be analysed for different times of the day and is a game changer – allowing Exterion to rethink how both their classic and digital inventory can be packaged and tailored specifically for clients. The presentation will cover how TfL and Exterion have collaborated, the approach used by TfL and how Exterion are using it to generate revenue which is reinvested in the transport network.

BDW17 London - Mick Ridley, Exterion Media & Dale Campbell , TfL - Transformi...

Big Data Week

Data Science is now well established in our businesses, and everyone considers data as a key asset and critical for our competitiveness. However, Data Science is not easy to manage, very often projects failed and the investment made is not seeing as profitable. The aim of this talk is to share the knowledge in different areas: * avoid classical mistakes in Data Science * use the right Big Data technology * apply the right methodology * make the Data Science team more efficient

BDW17 London - Abed Ajraou - First Utility - Putting Data Science in your Bus...

Big Data Week

BDW17 London - Steve Bradbury - GRSC - Making Sense of the Chaos of Data

Big Data Week

BDW17 London - Andy Boura - Thomson Reuters - Does Big Data Have to Mean Big ...

Big Data Week

BDW17 London - Tom Woolrich, Financial Times - What Does Big Data Mean for th...

Big Data Week

In this session, we’ll look at the key challenges of doing data science at scale – not just the mechanics of processing big data but the things that matter in putting our data to work. Things like how to work on that data in a multi-disciplinary team, how to set up and evaluate experiments and how to move from dev to test and production so those insights can be put to work across the business as needed. I will be showing how we do this at Microsoft, which might sound proprietary but actually is mainly about how we weave open source technologies together – technologies like Spark and Python, and containers.

BDW17 London - Andrew Fryer, Microsoft - Everybody Needs a Bit of Science in ...

Big Data Week

BDW16 London - Alex Bordei, Bigstep - Building Data Labs in the Cloud

Big Data Week

BDW16 London - William Vambenepe, Google - 3rd Generation Data Platform

Big Data Week

We have seen vast improvements to data collection, storage, processing and transport in recent years. An increasing number of networked devices are emitting data and all of us are preparing to handle this wave of valuable data. Have we, as data professionals, been too focused on the technical challenges and analytical results? What about the data quality? Are we confident about it? How can we be sure we are making good decisions? We need to revisit methods of assessing data quality on our modernized data platforms. The quality of our decision making depends on it.

BDW16 London - Scott Krueger, skyscanner - Does More Data Mean Better Decisio...

Big Data Week

BDW16 London - Nondas Sourlas, Bupa - Big Data in Healthcare

Big Data Week

Unsuccessful marketing campaigns are leaving customers disgruntled, making them 40% less likely to return. Companies are casting aside useful data that can provide further insights into better products/better connections with customers. John Callan, VP of Marketing at Boxever will discuss how AI can change how businesses predict trends, reduce risks, and improve efficiency. Audience will: Gain expert-level understanding of data and machine learning that’s used in today’s market Identify successful ways companies use machine learning to target customers with personalized content Learn from major airlines use-cases to skillfully target customers and show them exactly what they want to see.

BDW16 London - John Callan, Boxever - Data and Analytics - The Fuel Your Bran...

Big Data Week

Through the experiences of supporting a Multi-Country roll out using data to drive more effective Network capability, we will explain how we have: Created new internal capability to support local countries, developed skill sets in the country and provided technical infrastucture, algorithms and visualisations to drive the data culture and big data strategies across Telefonica business units. Through this framework, we will explain how to blend technical and business needs to maximise the benefits and drive better business performance.

BDW16 London - John Belchamber, Telefonica - New Data, New Strategies, New Op...

Big Data Week

The Basel Committee on Banking Supervision (BCBS) and local regulators has been focussed on making banks more safe and resilient. A whole raft of new capital charges and constraints on liquidity and leverage have been introduced: Basel II.5, Basel III, Dodd-Frank, FRTB (“Basel IV”), etc. These have significantly increased the risk data management capabilities banks must have—capabilities that only big data tools can provide. This talk will cover the challenges of building a position-aware risk management platform that properly aggregates all intra-day trading activity, monitors exposures and risk. The fast data stack can help banks create such a platform and provide a robust foundation to achieve compliance and, ultimately a significant competitive edge by making efficient use of capital.

BDW16 London - Deenar Toraskar, Think Reactive - Fast Data Key to Efficient C...

Big Data Week

BDW16 London - Jonny Voon, Innovate UK - Smart Cities and the Buzz Word Bingo

Big Data Week

BDW16 London - Marius Boeru, Bigstep - How to Automate Big Data with Ansible

Big Data Week

“At Shazam, we think data can be beautiful and stunningly inspiring. The pictures we paint with our data tell stories about changing culture, tastes, and shared discoveries. A truly great new song can sweep across the globe in a wave of Shazams that transcends politics, language, or religion”, Greg Glanday, Chief Revenue Officer at Shazam. This presentation will offer the audience a few examples of how they can use the data from Shazam to get fantastic insight into the consumers` preferences, and how to take that insight and apply it to a brand. Giving 3 or 4 great examples of what we do at Shazam, anyone in the audience can understand what this data means, really see this data and then be able to leverage it to make smart marketing decisions. Main takeaway: a clear understanding of what Shazam data is and how brands can use it.

BDW16 London - Josh Partridge, Shazam - How Labels, Radio Stations and Brand...

Big Data Week

More from Big Data Week (20)