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Big data is large and complex data that cannot be processed by traditional data management tools. It is characterized by high volume, velocity, and variety. Big data comes from many sources and in many formats, including structured, unstructured, and semi-structured data. Storing and processing big data requires specialized systems like Hadoop and NoSQL databases. Big data analytics can provide benefits like improved business decisions and customer satisfaction when applied to areas such as healthcare, security, and manufacturing. However, big data also presents risks regarding privacy, costs, and being overwhelmed by the volume of data.
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
Big Data Ppt PowerPoint Presentation Slides SlideTeam
Big data has brought about a revolution in the field of information technology. Our content-ready big data PPT PowerPoint presentation slides shed light on the importance and relevance of large volumes of data. The data management presentation covers myriad of topics such as big data sources, market forecast, 3 Vs, technologies, workflow, data analytics process, impact, benefit, future, opportunity and challenges, and many additional slides containing graphs and charts. The biggest benefit that this big data analytics presentation template offers is that it enables you to unearth the information that can be used to shape the future of your business. Moreover, these designs can also be utilized to craft your own presentation on predictive analytics, data processing application, database, cloud computing, business intelligence, and user behavior analytics. Download big data PPT visuals which will help you make accurate business decisions. Enlighten folks on fraud with our Big Data PPt PowerPoint Presentation Slides. Convince them to be highly alert.
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
We present you content-ready big data characteristics and process PowerPoint presentation that can be used to present content management techniques. It can be presented by IT consulting and analytics firms to their clients or company’s management. This relational database management PPT design comprises of 53 slides including introduction, facts, how big is big data, market forecast, sources, 3Vs and 5Vs small Vs big data, objective, technologies, workflow, four phases, types, information analytics process, impact, benefits, future, opportunities and challenges etc. Our data transformation PowerPoint templates are apt to present various topics such as information management concepts and technologies, transforming facts with intelligence, data analysis framework, data mining, technology platforms, data transfer and visualization, content management, Internet of things, data storage and analysis, information infrastructure, datasets, technology and cloud computing. Download big data characteristics and process PPT graphics to make an impressive presentation. Develop greater goodwill with our Big Data Characteristics And Process PowerPoint Presentation Slides. Folks feel friendlier towards you.
This document defines big data and discusses techniques for integrating large and complex datasets. It describes big data as collections that are too large for traditional database tools to handle. It outlines the "3Vs" of big data: volume, velocity, and variety. It also discusses challenges like heterogeneous structures, dynamic and continuous changes to data sources. The document summarizes techniques for big data integration including schema mapping, record linkage, data fusion, MapReduce, and adaptive blocking that help address these challenges at scale.
This document provides an overview of data science including what is big data and data science, applications of data science, and system infrastructure. It then discusses recommendation systems in more detail, describing them as systems that predict user preferences for items. A case study on recommendation systems follows, outlining collaborative filtering and content-based recommendation algorithms, and diving deeper into collaborative filtering approaches of user-based and item-based filtering. Challenges with collaborative filtering are also noted.
This document provides an overview of big data and how it can be used to forecast and predict outcomes. It discusses how large amounts of data are now being collected from various sources like the internet, sensors, and real-world transactions. This data is stored and processed using technologies like MapReduce, Hadoop, stream processing, and complex event processing to discover patterns, build models, and make predictions. Examples of current predictions include weather forecasts, traffic patterns, and targeted marketing recommendations. The document outlines challenges in big data like processing speed, security, and privacy, but argues that with the right techniques big data can help further human goals of understanding, explaining, and anticipating what will happen in the future.
Big data is large and complex data that cannot be processed by traditional data management tools. It is characterized by high volume, velocity, and variety. Big data comes from many sources and in many formats, including structured, unstructured, and semi-structured data. Storing and processing big data requires specialized systems like Hadoop and NoSQL databases. Big data analytics can provide benefits like improved business decisions and customer satisfaction when applied to areas such as healthcare, security, and manufacturing. However, big data also presents risks regarding privacy, costs, and being overwhelmed by the volume of data.
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
Big Data Ppt PowerPoint Presentation Slides SlideTeam
Big data has brought about a revolution in the field of information technology. Our content-ready big data PPT PowerPoint presentation slides shed light on the importance and relevance of large volumes of data. The data management presentation covers myriad of topics such as big data sources, market forecast, 3 Vs, technologies, workflow, data analytics process, impact, benefit, future, opportunity and challenges, and many additional slides containing graphs and charts. The biggest benefit that this big data analytics presentation template offers is that it enables you to unearth the information that can be used to shape the future of your business. Moreover, these designs can also be utilized to craft your own presentation on predictive analytics, data processing application, database, cloud computing, business intelligence, and user behavior analytics. Download big data PPT visuals which will help you make accurate business decisions. Enlighten folks on fraud with our Big Data PPt PowerPoint Presentation Slides. Convince them to be highly alert.
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
We present you content-ready big data characteristics and process PowerPoint presentation that can be used to present content management techniques. It can be presented by IT consulting and analytics firms to their clients or company’s management. This relational database management PPT design comprises of 53 slides including introduction, facts, how big is big data, market forecast, sources, 3Vs and 5Vs small Vs big data, objective, technologies, workflow, four phases, types, information analytics process, impact, benefits, future, opportunities and challenges etc. Our data transformation PowerPoint templates are apt to present various topics such as information management concepts and technologies, transforming facts with intelligence, data analysis framework, data mining, technology platforms, data transfer and visualization, content management, Internet of things, data storage and analysis, information infrastructure, datasets, technology and cloud computing. Download big data characteristics and process PPT graphics to make an impressive presentation. Develop greater goodwill with our Big Data Characteristics And Process PowerPoint Presentation Slides. Folks feel friendlier towards you.
This document defines big data and discusses techniques for integrating large and complex datasets. It describes big data as collections that are too large for traditional database tools to handle. It outlines the "3Vs" of big data: volume, velocity, and variety. It also discusses challenges like heterogeneous structures, dynamic and continuous changes to data sources. The document summarizes techniques for big data integration including schema mapping, record linkage, data fusion, MapReduce, and adaptive blocking that help address these challenges at scale.
This document provides an overview of data science including what is big data and data science, applications of data science, and system infrastructure. It then discusses recommendation systems in more detail, describing them as systems that predict user preferences for items. A case study on recommendation systems follows, outlining collaborative filtering and content-based recommendation algorithms, and diving deeper into collaborative filtering approaches of user-based and item-based filtering. Challenges with collaborative filtering are also noted.
This document provides an overview of big data and how it can be used to forecast and predict outcomes. It discusses how large amounts of data are now being collected from various sources like the internet, sensors, and real-world transactions. This data is stored and processed using technologies like MapReduce, Hadoop, stream processing, and complex event processing to discover patterns, build models, and make predictions. Examples of current predictions include weather forecasts, traffic patterns, and targeted marketing recommendations. The document outlines challenges in big data like processing speed, security, and privacy, but argues that with the right techniques big data can help further human goals of understanding, explaining, and anticipating what will happen in the future.
Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
Big Data: Its Characteristics And Architecture CapabilitiesAshraf Uddin
This document discusses big data, including its definition, characteristics, and architecture capabilities. It defines big data as large datasets that are challenging to store, search, share, visualize, and analyze due to their scale, diversity and complexity. The key characteristics of big data are described as volume, velocity and variety. The document then outlines the architecture capabilities needed for big data, including storage and management, database, processing, data integration and statistical analysis capabilities. Hadoop and MapReduce are presented as core technologies for storage, processing and analyzing large datasets in parallel across clusters of computers.
The document provides an overview of data science through an introduction by Sreejith C, a data scientist. It defines data science as discovering unknown information from data, obtaining predictive insights, creating impactful data products, and communicating business stories from data. A data scientist's work includes tasks like authoring data processing pipelines, performing analyses, and communicating results. The document also demonstrates a loan prediction problem using machine learning algorithms like logistic regression, decision trees, and random forests in Python.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
This document provides an introduction and overview of data science. It discusses Ravishankar Rajagopalan's educational and professional background working in data science. It then covers various topics related to data science including common applications, required skills, the typical project lifecycle, team aspects, career progression, interviews, and resources for learning. Examples of unusual real-world applications are also summarized, such as using machine learning to optimize inventory levels for an oil and gas company and implementing speech recognition to predict customer intent for a call center.
The document discusses big data analytics. It begins by defining big data as large datasets that are difficult to capture, store, manage and analyze using traditional database management tools. It notes that big data is characterized by the three V's - volume, variety and velocity. The document then covers topics such as unstructured data, trends in data storage, and examples of big data in industries like digital marketing, finance and healthcare.
This document provides an overview of big data, including its definition, characteristics, sources, tools, applications, risks and benefits. It defines big data as large volumes of diverse data that can be analyzed to reveal patterns and trends. The three key characteristics are volume, velocity and variety. Examples of big data sources include social media, sensors and user data. Tools used for big data include Hadoop, MongoDB and analytics programs. Big data has many applications and benefits but also risks regarding privacy and regulation. The future of big data is strong with the market expected to grow significantly in coming years.
1) The document introduces data science and its core disciplines, including statistics, machine learning, predictive modeling, and database management.
2) It explains that data science uses scientific methods and algorithms to extract knowledge and insights from both structured and unstructured data.
3) The roles of data scientists are discussed, noting that they have skills in programming, statistics, analytics, business analysis, and machine learning.
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 document provides an overview of getting started with data science using Python. It discusses what data science is, why it is in high demand, and the typical skills and backgrounds of data scientists. It then covers popular Python libraries for data science like NumPy, Pandas, Scikit-Learn, TensorFlow, and Keras. Common data science steps are outlined including data gathering, preparation, exploration, model building, validation, and deployment. Example applications and case studies are discussed along with resources for learning including podcasts, websites, communities, books, and TV shows.
This document provides an overview of key concepts related to data and big data. It defines data, digital data, and the different types of digital data including unstructured, semi-structured, and structured data. Big data is introduced as the collection of large and complex data sets that are difficult to process using traditional tools. The importance of big data is discussed along with common sources of data and characteristics. Popular tools and technologies for storing, analyzing, and visualizing big data are also outlined.
This document proposes a theme on big data analytics research. It notes that the world's data storage capacity doubles every 40 months and discusses how big data can provide value across many areas like health, policymaking, education and more. The proposal recommends that Hong Kong develop a state-of-the-art big data platform to make a difference in areas like smart cities and support aging populations. It outlines objectives like large-scale machine learning from big data and discusses how Hong Kong is well-positioned for this research with experts across universities and potential collaborators in industry. The expected outcomes include new methodologies, applications impacting society and industry, and educational programs to cultivate big data leaders.
What is Big Data?
Big Data Laws
Why Big Data?
Industries using Big Data
Current process/SW in SCM
Challenges in SCM industry
How Big data can solve the problems?
Migration to Big data for an SCM industry
This document provides an overview of big data and Hadoop. It defines big data as large volumes of diverse data that cannot be processed by traditional systems. Key characteristics are volume, velocity, variety, and veracity. Popular sources of big data include social media, emails, videos, and sensor data. Hadoop is presented as an open-source framework for distributed storage and processing of large datasets across clusters of computers. It uses HDFS for storage and MapReduce as a programming model. Major tech companies like Google, Facebook, and Amazon are discussed as big players in big data.
This document provides an overview of big data, including its definition, characteristics, sources, tools used, applications, benefits, and impact on IT. Big data is a term used to describe the large volumes of data, both structured and unstructured, that are so large they are difficult to process using traditional database and software techniques. It is characterized by high volume, velocity, variety, and veracity. Common sources of big data include mobile devices, sensors, social media, and software/application logs. Tools like Hadoop, MongoDB, and MapReduce are used to store, process, and analyze big data. Key applications areas include homeland security, healthcare, manufacturing, and financial trading. Benefits include better decision making, cost reductions
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
The document appears to be a presentation on big data. It includes slides on what big data is, facts about the size and growth of big data, sources of big data, the 3Vs and 5Vs models of big data, differences between small and big data, objectives and technologies of big data, the big data workflow, forms of big data, the data analytics process, impacts of big data, benefits of big data, the future of big data, and opportunities and challenges of big data. Additional slides provide templates that are editable for topics such as mission, team, about us, goals, comparisons, financials, quotes, dashboards, and locations.
Big Data Information Architecture Powerpoint Presentation SlideSlideTeam
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Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
Big Data: Its Characteristics And Architecture CapabilitiesAshraf Uddin
This document discusses big data, including its definition, characteristics, and architecture capabilities. It defines big data as large datasets that are challenging to store, search, share, visualize, and analyze due to their scale, diversity and complexity. The key characteristics of big data are described as volume, velocity and variety. The document then outlines the architecture capabilities needed for big data, including storage and management, database, processing, data integration and statistical analysis capabilities. Hadoop and MapReduce are presented as core technologies for storage, processing and analyzing large datasets in parallel across clusters of computers.
The document provides an overview of data science through an introduction by Sreejith C, a data scientist. It defines data science as discovering unknown information from data, obtaining predictive insights, creating impactful data products, and communicating business stories from data. A data scientist's work includes tasks like authoring data processing pipelines, performing analyses, and communicating results. The document also demonstrates a loan prediction problem using machine learning algorithms like logistic regression, decision trees, and random forests in Python.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
This document provides an introduction and overview of data science. It discusses Ravishankar Rajagopalan's educational and professional background working in data science. It then covers various topics related to data science including common applications, required skills, the typical project lifecycle, team aspects, career progression, interviews, and resources for learning. Examples of unusual real-world applications are also summarized, such as using machine learning to optimize inventory levels for an oil and gas company and implementing speech recognition to predict customer intent for a call center.
The document discusses big data analytics. It begins by defining big data as large datasets that are difficult to capture, store, manage and analyze using traditional database management tools. It notes that big data is characterized by the three V's - volume, variety and velocity. The document then covers topics such as unstructured data, trends in data storage, and examples of big data in industries like digital marketing, finance and healthcare.
This document provides an overview of big data, including its definition, characteristics, sources, tools, applications, risks and benefits. It defines big data as large volumes of diverse data that can be analyzed to reveal patterns and trends. The three key characteristics are volume, velocity and variety. Examples of big data sources include social media, sensors and user data. Tools used for big data include Hadoop, MongoDB and analytics programs. Big data has many applications and benefits but also risks regarding privacy and regulation. The future of big data is strong with the market expected to grow significantly in coming years.
1) The document introduces data science and its core disciplines, including statistics, machine learning, predictive modeling, and database management.
2) It explains that data science uses scientific methods and algorithms to extract knowledge and insights from both structured and unstructured data.
3) The roles of data scientists are discussed, noting that they have skills in programming, statistics, analytics, business analysis, and machine learning.
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 document provides an overview of getting started with data science using Python. It discusses what data science is, why it is in high demand, and the typical skills and backgrounds of data scientists. It then covers popular Python libraries for data science like NumPy, Pandas, Scikit-Learn, TensorFlow, and Keras. Common data science steps are outlined including data gathering, preparation, exploration, model building, validation, and deployment. Example applications and case studies are discussed along with resources for learning including podcasts, websites, communities, books, and TV shows.
This document provides an overview of key concepts related to data and big data. It defines data, digital data, and the different types of digital data including unstructured, semi-structured, and structured data. Big data is introduced as the collection of large and complex data sets that are difficult to process using traditional tools. The importance of big data is discussed along with common sources of data and characteristics. Popular tools and technologies for storing, analyzing, and visualizing big data are also outlined.
This document proposes a theme on big data analytics research. It notes that the world's data storage capacity doubles every 40 months and discusses how big data can provide value across many areas like health, policymaking, education and more. The proposal recommends that Hong Kong develop a state-of-the-art big data platform to make a difference in areas like smart cities and support aging populations. It outlines objectives like large-scale machine learning from big data and discusses how Hong Kong is well-positioned for this research with experts across universities and potential collaborators in industry. The expected outcomes include new methodologies, applications impacting society and industry, and educational programs to cultivate big data leaders.
What is Big Data?
Big Data Laws
Why Big Data?
Industries using Big Data
Current process/SW in SCM
Challenges in SCM industry
How Big data can solve the problems?
Migration to Big data for an SCM industry
This document provides an overview of big data and Hadoop. It defines big data as large volumes of diverse data that cannot be processed by traditional systems. Key characteristics are volume, velocity, variety, and veracity. Popular sources of big data include social media, emails, videos, and sensor data. Hadoop is presented as an open-source framework for distributed storage and processing of large datasets across clusters of computers. It uses HDFS for storage and MapReduce as a programming model. Major tech companies like Google, Facebook, and Amazon are discussed as big players in big data.
This document provides an overview of big data, including its definition, characteristics, sources, tools used, applications, benefits, and impact on IT. Big data is a term used to describe the large volumes of data, both structured and unstructured, that are so large they are difficult to process using traditional database and software techniques. It is characterized by high volume, velocity, variety, and veracity. Common sources of big data include mobile devices, sensors, social media, and software/application logs. Tools like Hadoop, MongoDB, and MapReduce are used to store, process, and analyze big data. Key applications areas include homeland security, healthcare, manufacturing, and financial trading. Benefits include better decision making, cost reductions
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
The document appears to be a presentation on big data. It includes slides on what big data is, facts about the size and growth of big data, sources of big data, the 3Vs and 5Vs models of big data, differences between small and big data, objectives and technologies of big data, the big data workflow, forms of big data, the data analytics process, impacts of big data, benefits of big data, the future of big data, and opportunities and challenges of big data. Additional slides provide templates that are editable for topics such as mission, team, about us, goals, comparisons, financials, quotes, dashboards, and locations.
Big Data Information Architecture Powerpoint Presentation SlideSlideTeam
Feel enthralled by all the attention by our Big data information architecture PowerPoint presentation slide offers. While designing the perfect framework for a durable system, it could get tricky to represent all the data in a systematic manner. Manifesting complex ideas in a simplified manner doesn't always comes handy. That's the reason we have well-researched formats and designs for professional and prolonging solutions. Our team of experts makes sure that all the PPT slides are framed to work for the best of the client. Numerous icons and images are used here for visual engagement. We have covered up every viewpoint of data structure possible, including, data market forecast, financial aspects, social media approach and different comparisons used in data analysis for an out of box view. Our sole and intriguing PowerPoint slides are your gateway to progress and serves you in holding your viewer's consideration towards the concept of discernment and improves the quality and accuracy of the business processes. Discourage injudicious comments with our Big Data Information Architecture Powerpoint Presentation Slide. Ensure folks adhere to the decorum. https://bit.ly/3g9RwnY
Big Data Ppt Powerpoint Presentation SlidesSlideTeam
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Data Management Analysis Powerpoint Presentation SlideSlideTeam
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Data Science Sources PowerPoint Presentation SlidesSlideTeam
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Big Data Governance Challenges Roadmap Processes Strategy Analytics DashboardSlideTeam
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Business Data Analytics Powerpoint Presentation SlidesSlideTeam
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Data Analytics PowerPoint Presentation SlidesSlideTeam
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Big Data Sources PowerPoint Presentation Slides SlideTeam
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Data Mining Sources PowerPoint Presentation SlidesSlideTeam
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Big Data Analytics PowerPoint Presentation Slides SlideTeam
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Big Data Analytics Powerpoint Presentation SlidesSlideTeam
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Presenting this set of slides with name - Big Data Analytics Powerpoint Presentation Slides. This exclusive deck with twenty slides is here to help you to strategize, plan, analyze, or segment the topic with clear understanding and apprehension. Utilize ready to use presentation slides on Big Data Analytics Powerpoint Presentation Slides with all sorts of editable templates, charts and graphs, overviews, analysis templates. You can change the colors, font, and text without any hassle to suit your business needs. Download PowerPoint templates in both widescreen and standard screen. The presentation is fully supported by Google Slides. It can be easily converted into JPG or PDF format. https://bit.ly/3KabVGz
Business Plan For Startup Funding Powerpoint Presentation SlidesSlideTeam
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Business Plan For Startup Funding PowerPoint Presentation SlidesSlideTeam
A business plan is a written document that describes in detail how a business, usually a new one, is going to achieve its goals. Keep the plan short and concise for easy readability. The enclosed simple business plan template is broken into sections to simplify the presentation. Use this Business plan PowerPoint template to carry out the smooth functioning of your start up. Organize the structural framework of your start up with the help of this business plan PPT layout. Make your business proposal impressive with this PowerPoint presentation. A precise plan can help you attract investors and financers for the funding of your start up. Highlight the interesting aspects of your business with the help of this business PPT design. Get this business PowerPoint presentation to state how the business intends to achieve its goals. Easily describe the operational activity and costs related to your start up with the help of this start up PowerPoint slides. Give a high-level overview of your business to your audience. This is the only time when the saying 'no pain no gain' doesn't holds true. Visually convincing Business Plan For Startup Funding Powerpoint Presentation Slides that everyone would love.
IT Security PowerPoint Presentation SlidesSlideTeam
Use IT security PowerPoint Presentation Slides to educate your audience about the cyber security. Incorporate professionally designed content-ready IT security PPT templates to showcase the techniques of protecting computers, networks, programs, and data from attacks that are aimed for exploitation. Demonstrate the preventive measures to protect information from being stolen, compromised or attacked with the help of IT security PowerPoint slideshow. Talk about various cybersecurity strategies which include identify management, risk management and incident management. This deck comprises of templates to create awareness regarding cyber security are cyber security seven preventive methods, cyber security framework, cyber security initiatives, cyber security tips, and more. Add relevant ready-to-use cyber security PPT templates to illustrate various tools such as software patches, firewalls, encryption, etc. These templates are completely editable. You can customize the template as per your convenience. Edit the color, text, icon, and font size as per your requirement. Download ready-made IT security PPT presentation to make your audience aware about the potential cyber threats. End the jitters with our It Security Powerpoint Presentation Slides. Don't give in to baseless apprehensions.
IT Security Powerpoint Presentation SlidesSlideTeam
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Use IT security PowerPoint Presentation Slides to educate your audience about the cyber security. Incorporate professionally designed content-ready IT security PPT templates to showcase the techniques of protecting computers, networks, programs, and data from attacks that are aimed for exploitation. Demonstrate the preventive measures to protect information from being stolen, compromised or attacked with the help of IT security PowerPoint slideshow. Talk about various cybersecurity strategies which include identify management, risk management and incident management. This deck comprises of templates to create awareness regarding cyber security are cyber security seven preventive methods, cyber security framework, cyber security initiatives, cyber security tips, and more. Add relevant ready-to-use cyber security PPT templates to illustrate various tools such as software patches, firewalls, encryption, etc. These templates are completely editable. You can customize the template as per your convenience. Edit the color, text, icon, and font size as per your requirement. Download ready-made IT security PPT presentation to make your audience aware about the potential cyber threats. End the jitters with our It Security Powerpoint Presentation Slides. Don't give in to baseless apprehensions. https://bit.ly/30N0fHN
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Presentation slides from XP2024 conference, Bolzano IT. The slides describe a new view to leadership and combines it with anthro-complexity (aka cynefin).
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Nathaniel Lane, Associate Professor in Economics at Oxford University, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by Yong Lim, Professor of Economic Law at Seoul National University School of Law, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
Carrer goals.pptx and their importance in real lifeartemacademy2
Career goals serve as a roadmap for individuals, guiding them toward achieving long-term professional aspirations and personal fulfillment. Establishing clear career goals enables professionals to focus their efforts on developing specific skills, gaining relevant experience, and making strategic decisions that align with their desired career trajectory. By setting both short-term and long-term objectives, individuals can systematically track their progress, make necessary adjustments, and stay motivated. Short-term goals often include acquiring new qualifications, mastering particular competencies, or securing a specific role, while long-term goals might encompass reaching executive positions, becoming industry experts, or launching entrepreneurial ventures.
Moreover, having well-defined career goals fosters a sense of purpose and direction, enhancing job satisfaction and overall productivity. It encourages continuous learning and adaptation, as professionals remain attuned to industry trends and evolving job market demands. Career goals also facilitate better time management and resource allocation, as individuals prioritize tasks and opportunities that advance their professional growth. In addition, articulating career goals can aid in networking and mentorship, as it allows individuals to communicate their aspirations clearly to potential mentors, colleagues, and employers, thereby opening doors to valuable guidance and support. Ultimately, career goals are integral to personal and professional development, driving individuals toward sustained success and fulfillment in their chosen fields.
2. Agenda
Text One
Text Two
Text Three
Text Four
Text Five
Text Six
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2
3. What is Big Data
Big Data
Big Data is characterized by
large volumes of different
types of data (e.g. social,
web, transaction, etc.) that
builds very quickly. It
exceeds the reach of
commonly used hardware
environments and software
tools to capture, manage and
process in a timely manner
for its users.
3
4. Big Data Facts-How Big is Big Data
Search queries
2 million
Google processes more than
Phone calls
300,000
Sprint processes more than
More than
100 million
New emails are generated
Twitter users send out
285,000
Tweets
Transactions
15,000
Walmart processes almost
New websites
576
Individuals and organizations launch
72 hours
of new video are uploaded to
YouTube
350 GB
of data
Facebook processes almost
12
3
6
9
4
5. How Big is Big Data
375
Megabytes
Data
consumed
by
households
each day
2.9
Million
Number Of
Emails
Sent Every
Second
24
Petabytes
Data per
day
processed
by google
20
Hours
Video
upload to
youtube
every
minute
700
Billion
Total
minutes
spent on
facebook
each
month
50
Million
Tweets
per
day
72.9
Items
Products
ordered
on
amazon
per
second
1.3
Exabytes
Data sent
and
received
by mobile
internet
users
5
6. Big Data Market Forecast
6
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S5.
1
2017
$48.0
2021
$32.1
2020
$16.8
2019
$10.2
2018
7. Sources of Big Data
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7
Images &
Media
Database
Locations
Email
Click
Stream
Social
Network
Html
Sensors
8. Sources of Big Data
Media
Media and communication
outlets (articles, podcasts,
audio, video, email, blogs)
Machine
Data generated by computers and
machines generally without human
intervention (business process
logs, sensors, phone calls)
Social
Digital material created by
social media (text, photos,
videos, tweets)
Historical
Data about our environment
(weather, traffic, census) and
archived documents, forms or
records
8
9. 3 Vs Of Big Data
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3 Vs of
Big Data
Variety
Velocity
Volume
• Terabytes
• Records
• Transactions
• Tables, files
• Batch
• Near time
• Semi structured
• Streams
• Structured
• Unstructured
• Semi structured
• All the above
9
10. 5 Vs Of Big Data
10
05
03
02
01
04
Variety
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Volume
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Velocity
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Value
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Veracity
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11. Small Data Vs Big Data
VS
Big Data
▪ Into Petabyte Volumes
▪ Real-time Velocities
▪ Multistructured Varieties
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Small Data
▪ Low Volumes
▪ Batch Velocities
▪ Structured Varieties
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12. Objective of Big Data
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Analyzing customer
behavior
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Combining multiple
data sources
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Improving
customer service
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Generate additional
revenue
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Be more responsive to
the market
01
02
03
04
05
Objective of
Big Data
12
13. Big Data Technologies
Data
Integration
Genetic
Algorithm
Machine
Learning
Natural
Language
Processing
Signal
Processing
Time
Series
Simulation
Crowd
Sourcing
Data
Fusion
Big Data
Technologies
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13
14. Big Data Workflow
14
Big Data
Actionable intelligence
Email
Click
stream
Html
Social
Location
Database
Sensor
data
Images
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15. Four Phases of Big Data
15
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Deposit
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Discover
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Decide
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Design
BIG DATA
01
02
04
03
16. Forms/Type of Big Data
WWW.COMPANY.COM 16
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Semi-Structured
Between the tow forms where
“tags” or “structure” are
associated or embedded
within unstructured data
Xml E- Mail Edi
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Unstructured
Data that does not reside
in fixed locations generally
refers to free-form text,
which is ubiquitous.
Databases Data
warehouses
Enterprise
systems
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Structured
Data that resides in
fixed fields within a
record or file.
Analog
data
GPS tracking
information
Audio/
video
streams
17. Data Analytics Process
Data
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Info
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Decision
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Insight
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18. Impact of Big Data
How Is Big
Data?
Sports predictions
Big data was used in 2012 to famously predict the
US would win 108 medals in the summer
Olympics. They won 104.
Easier commutes
Big data streamlines traffic, using data
from GPS systems. Traffic lights now
react to traffic conditions, weather &
accidents.
Smartphones
Smartphone users utilize big data
when asking for directions & verbally
asking their phone questions.
Advanced healthcare
Big data is used to predict where
outbreaks of potentially epidemic
viruses will occur.
Presidential campaigns
Statistician Nate silver used big data
to predict the outcome of the 2012
presidential election.
Personalized advertising
Big data is used to recommend
purchases & personalized ads
more relevant.
18
19. Impact of Big Data
01
Healthcare
it allow us to find new
cures and better
understand and predict
disease patterns. This
leads to saving more
lives.
02
Science
It creates new
possibilities and ways to
conduct research which
would otherwise be
impossible, helping us to
make new discoveries.
03
Security
Police forces use big
data tools to predict
criminal activities,
conduct investigations
and ultimately to catch
criminals faster.
04
Business
It helps us to improve
and optimize the ways
we do business by
making data-driven
decisions.
19
20. Benefits of Big Data
Increased
Efficiency
20% 35%
Better Business
Decision Making
50%
Improved customer
experience and
engagement
85%
Achieved
financial savings
20
21. Future of Big Data
85% of fortune 500
companies are ill prepared to
exploit big data
The digital universe is
doubling every 2 years, and
will reach 40,000 exabytes (40
trillion gigabytes) by 2020.
By 2015, 4.4 million IT jobs
globally will be created to support
Big Data, generating 1.9 million
IT jobs in the United States.
Fewer than 1 in 5 business
report being exactly where
they want to be in managing
and using data.
21
22. Big Data Opportunities and Challenges
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30% of it and business
executives are not familiar
with the phrase “Big Data”.
30%
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10% of companies looking
for skills in advanced
analytics/ predictive
analytics in the next 12
months.
10%
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50%
50% of companies do
not have a stated
Business Intelligence/
Analytics Strategy.
22
23. Big Data Opportunities and Challenges
23
Lack Of Sufficiently Skilled IT Staff
& Cost Of Technology
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Managing Data
Quality
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Data
Integration
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25. Our Mission
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01
02
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25
26. Managing Director
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John Carter
02
CEO/ Director
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Marry Smith
01
Finance Manager
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Sam John
04
Editor
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Anita Smith
03
Our Team
26
27. About Us
27
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Mark Hall
Graphic Designer
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Julie Hill
Web Designer
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Peter Tucker
Manager
28. Our Goal
28
03
02
01 04
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29. Comparison
80%
45%
60%
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31. Quotes
Be civil to all;
sociable to many;
familiar with few;
FRIEND
to one;
enemy to none.
- Benjamin Franklin
31
32. Dashboard
Your Text Here
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30%
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20%
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90%
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55%
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33. Location
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34. Timeline
2019
2018
2020
2021
2017
2022
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35. Post It
35
Text Here Text Here Text Here Text Here Text Here
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36. News Paper
NEWSPAPER
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37. Puzzle
37
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Here
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38. Target
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38
39. Circular
39
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your audience’s attention. 01
02
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04
05
06
07
08
40. Venn
01
02
03
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41. Mind Map
Text Here
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41
42. Matrix
High
Low High
02
01
03
04
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43. Lego
43
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44. Silhouettes
44
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46. Bulb or Idea
46
idea
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47. Magnifying Glass
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48. Bar Graph
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20%
30%
50%
60%
80%
90%
48
49. Funnel
49
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01
02
03
50. 50
Address
# street number, city, state
Contact Numbers:
08785644562
Email Address:
emailaddress123@.com
Thank You