Data is becoming an engine for many businesses in the information age, and every company needs to consider look at how that feels in their business model.
This an introductory guest lecture for students at Stockholm School of Entrepreneurship.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Data Driven Culture with Slalom's Director of AnalyticsPromotable
Everyone wants to capture the benefits of big data by making better data driven decision. We are inundated by analytical tools that deliver "insights" and process information quickly.
Although often overlooked, creating a data driven culture is as important as finding the right tools to make data driven decisions. Organizations who skip this foundational element often find their investment in Data tools and personal don't yield the benefits that becoming Data Driven is supposed to unlock.
In this talk you'll learn about why creating a Data Driven culture is vital to every organization and the starting point for ensuring your data strategy generates strong impact and ROI.
Takeaways:
What is a data driven culture? Where does it start?
What happens when you implement tools (tableau, power BI, Machine Learning, etc) without first having a data driven culture
Stages of a Data Driven Culture?
How to get started?
Your Instructor: Kevin Chapin is the Practice Director for Data and Analytics at Slalom Consulting.
To see the full talk, click here: https://www.youtube.com/watch?v=7xNLgiK31Is
RWDG Slides: The Stewardship Approach to Data GovernanceDATAVERSITY
Everybody in the organization is a data steward if they are held accountable for their relationship to data. Understanding who does what with the data is an easy way to recognize who your data stewards are. The data stewards are the people your Data Governance program will rely on.
Join Bob Seiner for this month’s webinar, where when he will focus on the role that lies at the heart of any approach to a Data Governance program. The first challenge of many programs is to recognize the stewards and assist them in seeing themselves in that important role.
In this webinar, Bob will discuss:
• Why everybody is a data steward
• The stewards’ impact on the complexity of your program
• How to leverage existing data responsibility
• Engaging stewards based on their relationship to data
• How to follow a Stewardship Approach
Data is becoming an engine for many businesses in the information age, and every company needs to consider look at how that feels in their business model.
This an introductory guest lecture for students at Stockholm School of Entrepreneurship.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Data Driven Culture with Slalom's Director of AnalyticsPromotable
Everyone wants to capture the benefits of big data by making better data driven decision. We are inundated by analytical tools that deliver "insights" and process information quickly.
Although often overlooked, creating a data driven culture is as important as finding the right tools to make data driven decisions. Organizations who skip this foundational element often find their investment in Data tools and personal don't yield the benefits that becoming Data Driven is supposed to unlock.
In this talk you'll learn about why creating a Data Driven culture is vital to every organization and the starting point for ensuring your data strategy generates strong impact and ROI.
Takeaways:
What is a data driven culture? Where does it start?
What happens when you implement tools (tableau, power BI, Machine Learning, etc) without first having a data driven culture
Stages of a Data Driven Culture?
How to get started?
Your Instructor: Kevin Chapin is the Practice Director for Data and Analytics at Slalom Consulting.
To see the full talk, click here: https://www.youtube.com/watch?v=7xNLgiK31Is
RWDG Slides: The Stewardship Approach to Data GovernanceDATAVERSITY
Everybody in the organization is a data steward if they are held accountable for their relationship to data. Understanding who does what with the data is an easy way to recognize who your data stewards are. The data stewards are the people your Data Governance program will rely on.
Join Bob Seiner for this month’s webinar, where when he will focus on the role that lies at the heart of any approach to a Data Governance program. The first challenge of many programs is to recognize the stewards and assist them in seeing themselves in that important role.
In this webinar, Bob will discuss:
• Why everybody is a data steward
• The stewards’ impact on the complexity of your program
• How to leverage existing data responsibility
• Engaging stewards based on their relationship to data
• How to follow a Stewardship Approach
Slides: Taking an Active Approach to Data GovernanceDATAVERSITY
A Look at How Riot Games Implemented Non-Invasive Data Governance
Riot Games created and runs “League of Legends,” the world’s most-played PC game and most viewed eSport — and is now transforming to become a multi-title publisher. To keep pace with this transformation and support a growing player base of millions, Riot Games is taking a page from Bob Seiner’s book, “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success” and leveraging the Alation Data Catalog to help guide accurate, well-governed analysis.
Bob Seiner will join Riot Games’ Chris Kudelka, Technical Product Manager, and Michael Leslie, Senior Data Governance Architect, and Alation’s John Wills, VP of Professional Service, for an inside look at Data Governance at one of the world’s leading gaming companies.
Join this webinar to learn:
• How Riot Games is implementing Non-Invasive Data Governance
• How this new approach to Data Governance helps to drive the business
• How the Alation Data Catalog helps Riot Games create the foundation for guiding accurate, well-governed data use
Big Data has been the big buzz word for companies. The problem is, no one told them what data to look at or more importantly what to do with the data. Learn what data to focus on and then how to create a process for your team to implement.
In times of digitalization, every aspect of our life is connected to data. To leverage this data, companies need to understand and master analytics. In this presentation, Leo Marose will guide you through the world of big data & data science and show you his approach of how to build a data-driven organization.
Met 80 procent van de klantdata wordt dit jaar niets gedaan. Hoeveel geld laat uw organisatie daardoor liggen? Data is geld waard. Bedrijven die vooruitdenken, managen hun data zo dat ze er winst uit halen. En dat geeft ze een flinke voorsprong.
Data Insights and Analytics: The Importance of Effective Communications in An...DATAVERSITY
Communicating analytics at your organization is more than just talking about the numbers. You’ll need to share insights and business impact – and do so in a way that resonates and informs well beyond the analysts and “data people.” The benefits to doing this are immense, including greater adoption and appreciation of the data, and a sustainable commitment to thoughtful, fact-based decision-making.
This webinar will offer tips and best practices for how to:
Effectively share data insights to convey business outcomes and actions, customizing for each audience
Grow your organization’s understanding of its data by being clear, concise, compelling, and candid
Utilize data visualization and data storytelling techniques and approaches
Think beyond the data by pulling in related research and findings to support or supplement key findings
Real-World Data Governance: Managing Governance Metadata for Mass ConsumptionDATAVERSITY
Metadata is a byproduct of a successful data governance program. More often than not, the success of a data governance program depends on the ability to record, validate and share metadata that is produced while implementing a data governance program. Metadata provides more than just the meaning of the data, the lineage of the data, and the rules associated with consuming the data. Governance metadata includes the people aspect of the data, who owns it (if you use that term), who stewards it, and who defines, produces and uses the data across the organization as well as other things.
Most companies do not think of data when they start out, let alone the quality of that data. With the proliferation of data and the usages of that data, organizations are compelled to focus more and more on data and their quality.
Join Kasu Sista of The Wisdom Chain to understand how to think about, implement, and maintain data quality.
You will learn about:
What do data people think about?
How do you get them to listen to what you want?
Business processes and data life span
Impact of data capture and data quality on down stream business processes
Data quality metrics and how to define them and use them
Practical metadata and data governance
What are the takeaways from the session?
How to talk to your data people
Understanding the importance of capturing data in the right way
Understanding the importance of quality metrics and bench marks
Understanding of operationalizing data quality processes
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
Social Data Week SF: Integrating Social and Enterprise Data for Competitive A...Social Data Week
Social Data should not be an island. It should be incorporated across the business for Social Data Intelligence. What is Social Data Intelligence? In her session at Social Data Week San Francisco, Susan Etlinger will explore the insight derived from social data that organizations can use confidently, at scale and in conjunction with other data sources to make strategic decisions.
Whitepaper: Thriving in the Big Data era Manage Data before Data Manages you Intellectyx Inc
Paper Overview -
Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.
Data comes from everywhere and we are generating data more than ever before.
This white paper will explain what Big Data is and provide practical examples, concluding with a message how to put data your data to work.
On this slides, we tried to give an overview of advanced Data quality management (ADQM). To understand about DQ why important, and all those steps of DQ management.
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Slides: Taking an Active Approach to Data GovernanceDATAVERSITY
A Look at How Riot Games Implemented Non-Invasive Data Governance
Riot Games created and runs “League of Legends,” the world’s most-played PC game and most viewed eSport — and is now transforming to become a multi-title publisher. To keep pace with this transformation and support a growing player base of millions, Riot Games is taking a page from Bob Seiner’s book, “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success” and leveraging the Alation Data Catalog to help guide accurate, well-governed analysis.
Bob Seiner will join Riot Games’ Chris Kudelka, Technical Product Manager, and Michael Leslie, Senior Data Governance Architect, and Alation’s John Wills, VP of Professional Service, for an inside look at Data Governance at one of the world’s leading gaming companies.
Join this webinar to learn:
• How Riot Games is implementing Non-Invasive Data Governance
• How this new approach to Data Governance helps to drive the business
• How the Alation Data Catalog helps Riot Games create the foundation for guiding accurate, well-governed data use
Big Data has been the big buzz word for companies. The problem is, no one told them what data to look at or more importantly what to do with the data. Learn what data to focus on and then how to create a process for your team to implement.
In times of digitalization, every aspect of our life is connected to data. To leverage this data, companies need to understand and master analytics. In this presentation, Leo Marose will guide you through the world of big data & data science and show you his approach of how to build a data-driven organization.
Met 80 procent van de klantdata wordt dit jaar niets gedaan. Hoeveel geld laat uw organisatie daardoor liggen? Data is geld waard. Bedrijven die vooruitdenken, managen hun data zo dat ze er winst uit halen. En dat geeft ze een flinke voorsprong.
Data Insights and Analytics: The Importance of Effective Communications in An...DATAVERSITY
Communicating analytics at your organization is more than just talking about the numbers. You’ll need to share insights and business impact – and do so in a way that resonates and informs well beyond the analysts and “data people.” The benefits to doing this are immense, including greater adoption and appreciation of the data, and a sustainable commitment to thoughtful, fact-based decision-making.
This webinar will offer tips and best practices for how to:
Effectively share data insights to convey business outcomes and actions, customizing for each audience
Grow your organization’s understanding of its data by being clear, concise, compelling, and candid
Utilize data visualization and data storytelling techniques and approaches
Think beyond the data by pulling in related research and findings to support or supplement key findings
Real-World Data Governance: Managing Governance Metadata for Mass ConsumptionDATAVERSITY
Metadata is a byproduct of a successful data governance program. More often than not, the success of a data governance program depends on the ability to record, validate and share metadata that is produced while implementing a data governance program. Metadata provides more than just the meaning of the data, the lineage of the data, and the rules associated with consuming the data. Governance metadata includes the people aspect of the data, who owns it (if you use that term), who stewards it, and who defines, produces and uses the data across the organization as well as other things.
Most companies do not think of data when they start out, let alone the quality of that data. With the proliferation of data and the usages of that data, organizations are compelled to focus more and more on data and their quality.
Join Kasu Sista of The Wisdom Chain to understand how to think about, implement, and maintain data quality.
You will learn about:
What do data people think about?
How do you get them to listen to what you want?
Business processes and data life span
Impact of data capture and data quality on down stream business processes
Data quality metrics and how to define them and use them
Practical metadata and data governance
What are the takeaways from the session?
How to talk to your data people
Understanding the importance of capturing data in the right way
Understanding the importance of quality metrics and bench marks
Understanding of operationalizing data quality processes
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
Social Data Week SF: Integrating Social and Enterprise Data for Competitive A...Social Data Week
Social Data should not be an island. It should be incorporated across the business for Social Data Intelligence. What is Social Data Intelligence? In her session at Social Data Week San Francisco, Susan Etlinger will explore the insight derived from social data that organizations can use confidently, at scale and in conjunction with other data sources to make strategic decisions.
Whitepaper: Thriving in the Big Data era Manage Data before Data Manages you Intellectyx Inc
Paper Overview -
Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone.
Data comes from everywhere and we are generating data more than ever before.
This white paper will explain what Big Data is and provide practical examples, concluding with a message how to put data your data to work.
On this slides, we tried to give an overview of advanced Data quality management (ADQM). To understand about DQ why important, and all those steps of DQ management.
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
The Role of Community-Driven Data Curation for EnterprisesEdward Curry
With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance. This chapter provides an overview of data curation, discusses the business motivations for curating data and investigates the role of community-based data curation, focusing on internal communities and pre-competitive data collaborations. The chapter is supported by case studies from Wikipedia, The New York Times, Thomson Reuters, Protein Data Bank and ChemSpider upon which best practices for both social and technical aspects of community-driven data curation are described.
E. Curry, A. Freitas, and S. O’Riáin, “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood, Ed. Boston, MA: Springer US, 2010, pp. 25-47.
Data-driven decision-making is an incredible process that helps data science professionals boost their businesses. Explore DDDM in detail and learn how you can master it in 2024
NTEN Your Analytics doesn't have to be dramatic to be usefulAndrew Patricio
My presentation at the 2024 NTEN conference in Portland, OR. I talk about practical approaches and benefits to deploying your analytics and reporting systems. Three high level themes:
1. Focus on people not the system, in particular make sure you start with hiring someone who understands your data before building your system. Data analytics augments human intuition not replaces it.
2. Make sure you start with your organizational vision to define your business outcomes to define your metrics and analytics to define your data. In other words make sure you are tracking relevant data
3. It is more about evolution not revolution. Data science is incremental not sudden.
1. Sepa exactamente de donde provienen sus datos.
2. Asegure que todos en la organización comparten los mismos datos, con un acceso fácil y libre de complejidades.
3. Gobernabilidad de la información: mantenga a su equipo capacitado en procesos simples y transparentes.
Predictive Analytics - How to get stuff out of your Crystal BallDATAVERSITY
Everyone wants to leverage data. The optimal implementation of analytics is an organization-wide set of capabilities. These are called advantageous organizational analytic capabilities in that a clear ROI is demonstrable from these efforts. Turns out that there are a number of prerequisites to advantageous organizational analytics. These include:
Adopting a crawl, walk, run strategy
Understanding current and potential organizational maturity and corresponding capabilities
Achieving an appropriate technology/human capability balance
Implementing useful IT systems development practices
Installing necessary non-IT leadership
This webinar will explore these and other topics using examples drawn from DOD, healthcare researchers, and donation center operations.
Data security, quality and process transparency are areas that are posing risks for organisations in the age of Big and Small Data. In this presentation I define the problem and present some solutions to bridge the Data Governance chasm.
Data Innovation Summit: Data Integrity TrendsPrecisely
Data integrity remains an evolving process of discovery, identification, and resolution. With an all-time low in public confidence on data being used for decision-making, attention has gradually shifted to data quality and data integration across multiple systems and frameworks. Data integrity becomes a focal point again for companies to make strategic moves in a world facing an evolving economy.
Key takeaways:
· How to build a data-driven culture within your organization
· Tips to engage with key stakeholders in your business and examples from other businesses around the world
· How to establish and maintain a business-first approach to data governance
· A summary of the findings from a recent survey of global data executives by Drexel University's LeBow College of Business
Panelists from a large company, a small company and a software consulting firm will share insights on how their companies are tackling the arena of Big Data and how to leverage a variety of data sources for strategic decision-making.
Foundational Strategies for Trust in Big Data Part 2: Understanding Your DataPrecisely
Teams working on new initiatives whether for customer engagement, advanced analytics, or regulatory and compliance requirements need a broad range of data sources for the highest quality and most trusted results. Yet the sheer volume of data delivered coupled with the range of data sources including those from external 3rd parties increasingly precludes trust, confidence, and even understanding of the data and how or whether it can be used to make effective data-driven business decisions.
The second part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Trillium Discovery for Big Data with its natively distributed execution for data profiling supports a foundation of data quality by enabling business analysts to gain rapid insight into data delivered to the data lake without technical expertise.
This presentation explores the goals of today's data-driven organizations, the challenges imposed by external macro forces, and the imperative for data integrity to enable innovation and drive business success. Learn about the key insights and findings from the latest global survey of over 400 global data professionals, the 2023 Data Integrity Trends and Insights report.
Data Profiling: The First Step to Big Data QualityPrecisely
Big data offers the promise of a data-driven business model generating new revenue and competitive advantage fueled by new business insights, AI, and machine learning. Yet without high quality data that provides trust, confidence, and understanding, business leaders continue to rely on gut instinct to drive business decisions.
The critical foundation and first step to deliver high quality data in support of a data-driven view that truly leverages the value of big data is data profiling - a proven capability to analyze the actual data content and help you understand what's really there.
View this webinar on-demand to learn five core concepts to effectively apply data profiling to your big data, assess and communicate the quality issues, and take the first step to big data quality and a data-driven business.
Noise to Signal - The Biggest Problem in DataDATAVERSITY
Our ability to produce, ingest and store data has grown exponentially, but our ability to parse out insights from data has not. In the 90s, an organization’s data would live in a data warehouse with an ETL pipeline and one reporting layer on top. Information was well controlled if not somewhat limited in breadth and slow to trickle down. Now with the onset of self-service analytics, anyone can create a report and an insight and there are many different sources of “truth.” For example, a seemingly straightforward question like "how many customers do we have?" will likely return difference answers from sales, finance and customer success, depending on their definitions and the data at hand. There is simply too much data (and duplicate data), too many tools, and too many systems storing data -- leading to time consuming searches, confusion and a lack of trust. Hear Stephanie discuss how a data catalog can help solve the noise to signal problem - making information easier to find, easier to understand and more trustworthy. She will describe how organizations like Safeway, Albertsons, Munich Re and Pfizer leverage a data catalog to find data and collaborate on data, gain a fuller understanding of its meaning and ultimately, solve important problems.
Applying Data Quality Best Practices at Big Data ScalePrecisely
Global organizations are investing aggressively in data lake infrastructures in the pursuit of new, breakthrough business insights. At the same time, however, 2 out of 3 business executives are not highly confident in the accuracy and reliability of their own Big Data. Regaining that confidence requires utilizing proven data quality tools at Big Data scale.
In this on-demand webinar, discover how to ensure your data lake is a trusted source for advanced business insights that lead to new revenue, cost savings and competitiveness. You will have the opportunity to:
• Compare your organization’s data lake “readiness” against initial findings from our upcoming annual Big Data Trends survey
• Gain insight into where and how to leverage data quality best practices for Big Data use cases
• Explore how a ‘Develop Once, Deploy Anywhere’ approach, including to native Big Data infrastructures such as Hadoop and Spark, facilitates consistent data quality patterns
Data integration and governance drive value by enabling organizations to achieve more accurate, reliable, and comprehensive insights from their data. Learn about different approaches and best practices to enhance your data integration and governance strategy.
Click here to download your eBook:
https://resources.pixentia.com/how-data-integration-and-governance-enables-hr-to-drive-value
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
12. If no one trusts your data, it’s essentially useless.
Everyone can access the same quality data
Garbage in – Garbage out (GIGO)
Data catalogs act as guides
Data governance as part to being data-driven
15. Data Democrazitation
Make data available to the people
Access to data that can help business users
Users are finding ways to liberate that data on their own
16. Open point for Data Democrazitation
Unregulated access to data
Siloed projects put compatibility, compliance, and security at risk
Who owns data and what its intended purpose is
17. „Every employee should be empowered to make data informed
decisions.“
„In order to inform every decision with data, it wouldn’t be possible to
have a data scientist in every room — we needed to scale our skillset.“
28. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context
29.
30. Being data-informed, not data-driven
-12% engagement (time spent in product) and neutral conversion
+22% conversion, with engagement staying neutral
„We weren’t binary, we didn’t throw it away completely at the first sign
of trouble.“
Alastair Simpson
31. „Data and A/B test are valuable allies, and they help us understand and
grow and optimize, but they’re not a replacement for clear-headed,
strong decision-making.“
„Don’t become dependent on their allure. Sometimes, a little instinct
goes a long way.“
Julie Zhuo
Facebook Product Director
32. Context-driven visualization
Not everything that can be counted counts, not everything that counts
can be counted.
Qlik DataMarket as integrated DaaS (data as-a-service) offering
So you used the data to inform you, but ultimately the deciding factor
was you.
33. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
34. Analytics is about impact
No change -> zero credit
Tie actions to outcome
Distill it down to actionable insights.
These insights should drive real-time decision
35. Ensure that insights lead to action
1. How will data visualizations be distributed?
2. Do you have the right people available who can review the data?
3. What existing KPIs and measures will be disrupted?
4. Who is likely to support this change?
5. Who is likely to resist it?
36. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture
37. Definition of culture
„The way we do things around here.“
„How data is used to organize activities, make decisions and resolve
conflict.“
38. „Data-driven companies establish processes and operations to make it
easy for employees to acquire the required information, but are also
transparent about data access restrictions and governance methods.“
39. Infonomics
How do you measure the value of information?
Treating data as an enterprise asset in everyday practice.
Information's value in terms of its realized value and potential value.
40. Ability to confront the brutal facts
If the data tells you bad news
The human, financial and reputational impacts can be devastating
41. Data-driven culture
Lives and dies by example behavior
Executives are looking for the right data to base decisions on
Communication about how data-driven their decision making has been
42.
43. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation
44.
45.
46. How to start? Simply step back and ask.
1. What does this mean for the business?
2. Can I even trust these numbers?
3. Does this mean what I think it means?
4. What tracking should be in place?
5. Is this data usable and accessible by the teams?
47. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
48. Data integrity
„Data integrity can be described as the accuracy and consistency of
data throughout its entire lifecycle of being used by business or
technical processes.“
Keith Furst
53. Compliance risk in ETL process
Was all of the data extracted properly?
Was all of the data transformed from the source to the target system
as designed?
Was all of the data loaded from the source to the target system
successfully?
54. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
55. Take the time to ask critical questions
Being good at analytics is about asking good questions.
More data isn’t always a good thing; if it’s poor quality data, you may
just be more confident in making bad decisions.
Take the time to ask critical questions
56. Take away
Developing a fully optimized data-driven capability can be difficult and
costly, but getting started doesn't have to be.
Hackathon is the perfect chance to show off your #QlikSense skills –
and have fun too!
57. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
58. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
