The document discusses how marketing analytics uses procedures and technologies to assess the success of marketing initiatives by estimating performance metrics. It aims to determine how marketing analytics benefits from big data and its implications for Ireland's retail sector. Specifically, it investigates how big data can help existing market analytic processes and how the Irish retail market can benefit from integrating big data-driven market analytics.
Business Analytics and Optimization Introduction (part 2)Raul Chong
Technical introduction to Business Analytics and optimization. This is part 2. Part 1 can be found here: http://www.slideshare.net/rfchong/business-analytics-and-optimization-introduction
A changing market landscape and open source innovations are having a dramatic impact on the consumability and ease of use of data science tools. Join this session to learn about the impact these trends and changes will have on the future of data science. If you are a data scientist, or if your organization relies on cutting edge analytics, you won't want to miss this!
This tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine learning models are needed in healthcare and how they should be deployed. Additionally, we explore the landscape of recent advances to address the challenges model interpretability in healthcare and also describe how one would go about choosing the right interpretable machine learnig algorithm for a given problem in healthcare.
Business Analytics and Optimization Introduction (part 2)Raul Chong
Technical introduction to Business Analytics and optimization. This is part 2. Part 1 can be found here: http://www.slideshare.net/rfchong/business-analytics-and-optimization-introduction
A changing market landscape and open source innovations are having a dramatic impact on the consumability and ease of use of data science tools. Join this session to learn about the impact these trends and changes will have on the future of data science. If you are a data scientist, or if your organization relies on cutting edge analytics, you won't want to miss this!
This tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine learning models are needed in healthcare and how they should be deployed. Additionally, we explore the landscape of recent advances to address the challenges model interpretability in healthcare and also describe how one would go about choosing the right interpretable machine learnig algorithm for a given problem in healthcare.
This presentation aims to bring into your knowledge, the various open source ERPs available in the market. I have compared various ERPs to choose best for required business model. Note: Different model may require different type of ERPs.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Slides used for a presentation to introduce the field of business analytics. Covers what BA is, how it is a part of business intelligence, and what areas make up BA.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Introduction to Data Science and AnalyticsSrinath Perera
This webinar serves as an introduction to WSO2 Summer School. It will discuss how to build a pipeline for your organization and for each use case, and the technology and tooling choices that need to be made for the same.
This session will explore analytics under four themes:
Hindsight (what happened)
Oversight (what is happening)
Insight (why is it happening)
Foresight (what will happen)
Recording http://t.co/WcMFEAJHok
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
My presentation at The Richmond Data Science Community (Jan 2018). The slides are slightly different than what I had presented last year at The Data Intelligence Conference.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Being able to make data driven decisions is a crucial skill for any company. The requirements are growing tougher - the volume of collected data keeps increasing in orders of magnitude and the insights must be smarter and faster. Come learn more about why data science is important and what challenges the data teams need to face.
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
Exploratory data analysis data visualization:
Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to
Maximize insight into a data set.
Uncover underlying structure.
Extract important variables.
Detect outliers and anomalies.
Test underlying assumptions.
Develop parsimonious models.
Determine optimal factor settings
This video will give you an idea about Data science for beginners.
Also explain Data Science Process , Data Science Job Roles , Stages in Data Science Project
This presentation aims to bring into your knowledge, the various open source ERPs available in the market. I have compared various ERPs to choose best for required business model. Note: Different model may require different type of ERPs.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Slides used for a presentation to introduce the field of business analytics. Covers what BA is, how it is a part of business intelligence, and what areas make up BA.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Introduction to Data Science and AnalyticsSrinath Perera
This webinar serves as an introduction to WSO2 Summer School. It will discuss how to build a pipeline for your organization and for each use case, and the technology and tooling choices that need to be made for the same.
This session will explore analytics under four themes:
Hindsight (what happened)
Oversight (what is happening)
Insight (why is it happening)
Foresight (what will happen)
Recording http://t.co/WcMFEAJHok
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
My presentation at The Richmond Data Science Community (Jan 2018). The slides are slightly different than what I had presented last year at The Data Intelligence Conference.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Being able to make data driven decisions is a crucial skill for any company. The requirements are growing tougher - the volume of collected data keeps increasing in orders of magnitude and the insights must be smarter and faster. Come learn more about why data science is important and what challenges the data teams need to face.
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
Exploratory data analysis data visualization:
Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to
Maximize insight into a data set.
Uncover underlying structure.
Extract important variables.
Detect outliers and anomalies.
Test underlying assumptions.
Develop parsimonious models.
Determine optimal factor settings
This video will give you an idea about Data science for beginners.
Also explain Data Science Process , Data Science Job Roles , Stages in Data Science Project
Driving Marketing Efficiency In The Consumer Goods Business With Advanced Ana...Gina Shaw
"Information is the oil of the 21st century, and analytics is the combustion engine" – Gartner
A large percentage of marketing efforts in a consumer goods business has little to no impact on sales. One primary reason for low-yield marketing campaigns is the inability to leverage data. Success in the consumer goods industry largely depends on the speed and accuracy of decision-making.
This eBook will help you discover:
1. Challenges marketers face in in the consumer goods business
2. The current state of marketing analytics
3. The overview and importance of advanced analytics
4. Traditional analytics vs advanced analytics
5. Advanced analytics solutions use cases in the areas of
- Measuring marketing effectiveness
- Optimizing marketing and advertising spend
- Sales forecasting
- Product portfolio management
- Marketing mix modelling
6. Driving analytics adoption within your organization with AI
7. Case study: How a global CPG company reduced marketing spend by 5% with advanced analytics
8. How you can get started right away?
Banalytics - Monetizing corporate big data | InstareaMatej Misik
How to use corporate big data for external applications, remain legally and ethically compliant and create a solution with clear public good? At the marketing edition of Banalytics in Bratislava, Matej Misik shared our approach to big data monetization for telcos, banks and other data rich industries.
Instarea is a "laboratory" for innovative big data monetization ideas within the international Adastra group. A young committed team, fresh thinking and a lust for adventure define us as a company. We yearn to change the world for the better through data.
1 Five Big Data Trends Revolutionizing Retail Summary.docxjeremylockett77
1
Five Big Data Trends Revolutionizing Retail
Summary: More retailers are finding that Big Data can revitalize an industry challenged by a slow economy,
increasingly empowered consumers, mobile proliferation and an ever-growing number of channels.
By Andrew Brust for Big on Data | August 16, 2013 --
This guest post is from Kelly Kennedy, Senior Vice President of Enterprise Sales at Info group Targeting
Solution
s, where she supports large
enterprise clients with a wealth of industry experience across both B2C and B2B solutions.
By Kelly Kennedy
Its Moore’s law of marketing: The aggregate amount of data available to retailers doubles every two years. Acquiring the
insights that retailers need to find, target and retain their ideal customers used to be a problem. Now, marketers are tasked
with sifting through the enormous amount of data they have on hand. Big Data is just that, and the sheer amount makes it
difficult not only to discern what’s valuable, but to discover what information might be missing or lost in the shuffle.
The retail industry may have turned a corner. In a recent interview, Karem Tomak, vice president of analytics for
Macys.com, admitted that just three years ago the department store relied on Excel spreadsheets to house and make sense
of customer data. Now the retail giant is crediting Big Data and analytics with a double-digit percentage increase in
revenue.
More retailers are finding that Big Data has the potential to revitalize an industry being challenged by a slow economy,
increasingly empowered consumers, mobile proliferation and an ever-growing number of channels. Although Big Data is
having profound impacts on retail and marketing strategy, it’s important for brands to use these trends as building blocks
for a greater process flow overhaul. Without the proper technology, internal knowledge and best practices in place, it’s
difficult to maximize Big Data’s potential benefits.
Five ways Big Data is revolutionizing retail marketing
1. Growing, cross-channel data volumes
The rise of mobile, tablets and social media has accelerated the growth of available customer
data. A typical retailer knows not only the basic demographic information about a customer, but
purchase history, call center interaction, mobile/social interaction, supply chain data and more.
The sheer volume of information available to retailers is unprecedented, even for brands that
have years of experience analyzing customer data.
2. Increasing investment in technology
You’d be hard-pressed to walk into a Best Buy right now and find a hard drive that stores less
than a terabyte. Storage is so cheap that it’s leveling the playing field for many companies when
it comes to Big Data. Retail leaders have started investing in centralized databases and focusing
on data hygiene and analytics, giving them insight into their customers that wasn't possible even
a few years ago.
In 2013, retailer ...
Marketing & SalesBig Data, Analytics, and the Future of .docxalfredacavx97
Marketing & Sales
Big Data, Analytics,
and the Future of
Marketing & Sales
March 2015
3McKinseyonMarketingandSales.com @McK_MktgSales
Table of contents
Business
Opportunities
Insight and
action
How to get
organized and
get started
8 Getting big impact from big
data
16 Big Data & advanced
analytics: Success stories
from the front lines
20 Use Big Data to find
new micromarkets
24 Smart analytics: How
marketing drives short-term
and long-term growth
30 Putting Big Data and
advanced analytics to work
34 Know your customers
wherever they are
38 Using marketing analytics to
drive superior growth
48 How leading retailers turn
insights into profits
56 Five steps to squeeze more
ROI from your marketing
60 Using Big Data to make
better pricing decisions
60 Marketing’s age of relevance 72 Gilt Groupe: Using Big Data,
mobile, and social media to
reinvent shopping
76 Under the retail microscope:
Seeing your customers for
the first time
80 Name your price: The power
of Big Data and analytics
84 Getting beyond the buzz: Is
your social media working?
90 How to get the most from big
data
94 Five Roles You Need on Your
Big Data Team
98 Want big data sales programs
to work? Get emotional
102 Get started with Big Data:
Tie strategy to performance
106 What you need to make Big
Data work: The pencil
110 Need for speed: Algorithmic
marketing and customer
data overload
114 Simplify Big Data – or it’ll be
useless for sales
54 McKinseyonMarketingandSales.com @McK_MktgSales
Introduction
Big Data is the biggest hame-changing opportunity for marketing and sales
since the Internet went mainstream almost 20 years ago. The data big bang
has unleashed torrents of terabytes about everything from customer behaviors
to weather patterns to demographic consumer shifts in emerging markets.
The companies who are successful in turning data into above-market growth
will excel at three things:
ƒ Using analytics to identify valuable business opportunities from the data to
drive decisions and improve marketing return on investment (MROI)
ƒ Turning those insights into well-designed products and offers that delight
customers
ƒ Delivering those products and offers effectively to the marketplace.
This goldmine of data represents a pivot-point moment for marketing and
sales leaders. Companies that inject big data and analytics into their operation
show productivity rates and profitability that are 5 percent to 6 percent hight
than those of their peers. That’s an advantage no company can afford to
gnome.
This compendium explores the business opportunities, company examples,
and organizational implications of Big Data and advanced analytics. We hope
it provokes good and useful conversations.
Please contact us with your reactions and thoughts.
David Court
Director
David headed McKinsey’s
functional practices, and
currently leads the firm’s digital
in.
The days of casting marketing dollars into the abyss and hoping for the best are ancient history. Marketing analytics has transformed from a nice-to-have into an absolute necessity for businesses. As we step into the marketing landscape of 2024, this report is your key to unlocking the secrets, strategies, and trends that will shape the… Continue reading The Future of Marketing Analytics 2024 Predictions Unveiled
Business Intelligence, Data Analytics, and AIJohnny Jepp
Data is the new currency. In this session, best practices on data collection, management dashboards, and used cases will be shared using Azure Data Services.
Video accessible at bit.ly/APACSummitOnDemand
Shwetank Sheel
Chief Executive Officer
Just Analytics
Poonam Sampat
Cloud Solution Architect - Data & AI
Microsoft Asia Pacific
Marketing automation market report by marketsand marketsDheerajPawar4
Marketing Automation Market by Component (Software, Services), Organization Size, Applications (Lead Nurturing & Lead Scoring, Email Marketing, Social Media Marketing, Analytics & Reporting, Campaign Management), Industry & Region - Global Forecast to 2024
Similar to Poster presetation for "Using Big Data for Marketing Analytics" (20)
The research follows an identification of the marketing analytics using the big data concept within the Irish retail market. This follows emphasizing on the benefits that the Irish retail companies have experienced in their marketing activities and the challenges they have faced in the process. The research carries out a thorough monitoring and evaluation thereby carrying out qualitative data analysis that has helped to identify the viewpoints of both the company’s employees and managers. This has helped to understand the internal impact and developments that have been brought about in the process.
Further emphasis is laid on locating the various aspects of the Big Data process thereby emphasizing on the various marketing operations within the company thereby conducting the research aims and objectives accordingly. This helped to develop suitable aims and objectives, followed by the major goals behind utilizing the concept within the company, and how far have they been benefited in the process. Further emphasis was laid on the ‘Ideal customer profile’, which has helped the company to set their targets effectively thereby using the best big data technologies to diversify the business (Ducange et al. 2018). The marketing analytics has helped to strike on the balance that lies between the big data concept and the knowledge fusion taxonomy, which has helped to identify the various degrees of complexity within the market (Abbasi et al. 2016). The use of the marketing and sales of Big Data has greatly been able to widen the opportunities of marketing thereby emphasizing on the customer preferences duly. This has further in turn helped to diversify any business integrated marketing management strategies thereby optimizing the marketing programs (Gunasekaran et al. 2017).
Marketing plan for new feature of airbnbTouseef Ahmed
analysis of the positive and negative impacts of the environment on Airbnb. Examine the company’s marketing strategy and the factors contributing towards Airbnb’s success. Devising a marketing plan that could envision the company towards higher performance.
This is a marketing plan for Enlil vertical axis wind turbine invented by Deveci tech labs. This marketing plan is for Ireland market. This is a group assignment created by a group of MBA students of Dublin Business School.
Egypt as a potential market for foreign and home-grown industriesTouseef Ahmed
Analysis of Egypt as a potential market for foreign and home-grown industries in the next years. Entry modes for a foreign company to set itself into Egyptian market.
Facebook as communications tool in the digital age for marketersTouseef Ahmed
The upcoming of social media networks has altered the ways individuals interact with families, friends, businesses, and even strangers. Since, Social media is used as a communications medium, therefore it can rightly be said as a tool to reach out to that population already present on the platform. As per Statista, there are around 2.46 billion active social media users in and around the world. This is expected to grow to 2.77 billion users until 2019. An average user spent 135 minutes over Social media platform in 2017 as compared to 90 minutes spent over social media in 2012. Globally, total number of social network users surpassed the count of 2 billion users in 2016.
Facebooks Usefulness to Marketers / AdvertisersTouseef Ahmed
As per Statista, an average user spent 135 minutes over Social media platform in 2017 as compared to 90 minutes spent over social media in 2012. [Refer to link: Average daily time spent on social media worldwide 2012-2017]. And Facebook being the biggest and most popular Social media is therefore the largest platform for opportunity seekers. Facebook currently has 2.2 billion active monthly users. This makes it a hotspot over the internet for companies to advertise/market their products over the Facebook platform. Advertisers/marketeers run campaigns and advertisements to try and reach those 2.2 billion active users who could potentially buy their product and become their customer at the same time in the longer run.
Some of the Facebook advertising features include:
• Demographic targeting by Facebook user data on age, location, education, and interests.
• The ability to set ad budgets.
• Ad testing, in which multiple ad versions can be run simultaneously in order to compare ad designs and setup.
• Built-in ad performance measurement tools.
Business Strategy Analysis of The Global Pharmaceutical IndustryTouseef Ahmed
The global pharmaceutical industry is considered as one of the essential industries present in every country. The global pharmaceutical industry manufactures a variety of medicines. These industries generally produce licensed drugs that are generally used for the purpose of medication. Their R&D department is well equipped for the production of the licensed drugs used for medication. The pharmaceutical industries generally deal with medications that are branded or generic and medical devices and tools (DiMasi et al. 2016). They need to follow a number of laws and regulations of the government that are concerned with the patenting, testing, pricing and they need to guarantee safety and the efficiency and marketing of the drugs.
This study regarding the global pharmaceutical industry actually describes the changes that occurred in the industry since the beginning and its environment, facilities, its success factors etc. Lastly, this study will provide an overall view of the future prospects of the global pharmaceutical industries based on the analysis that will be done in this study.
Developing strategic operations in an organization is liable to develop effective regulative operations within the company and the output of such implementation can be assessed through its adoption in the market. Hence, the assignment has investigated assessing various areas of operational perspectives of Unilever. Therefore, finding the reason behind the success of the organization that is implicating on its services is the core focus of the assignment. Initiation of the assignment is focused on analyzing Unilever’s capabilities that relates to key success factors of the organization. proceeding through Unilever’s stakeholder integration, the cultural diversity in the organization is also aimed to be discussed within the assignment. Finally, the assignment has aimed in developing suggestions depending on the study that it will make through the course of discussion considering its effects on the growth of the company.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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.