You're about to create your best presentation ever

Big Data Presentation Background

Create your presentation by reusing one of our great community templates.

Big Data Presentation

Transcript: Case study - the use of facial recognition technology at Amsterdam Schiphol Airport, a pilot project Paula Vermelho Cordiolli, Ingrid Quinn, Melike Babur Baran Introduction & Overview Scope & limitations of fundamental rights as applied to use of FRT (for national security, border control) Use of FRT: Compliance-Non-compliance with EU HR Law Private and public sector obligations Challenges, gaps, opportunities Analysis and Conclusion Introduction Main stakeholders: Amsterdam Schiphol Airport Royal Netherlands Marechaussee (KMar) Cathay Pacific Vision Box Introduction Introduction Main points: The program's goal is the development of self-boarding technology, by which the passengers will be able to pass through the Schiphol checkpoints by facial recognition Procedure Regulation EU laws & regulations Treaty on European Union (TEU) Main aspects: Human Rights Data Protection Border Control Other relevant principles: Respect for private life and protection of personal data Non-discrimination Rights of the child and of elderly people Freedom of expression and freedom of assembly and of association Right to good administration Right to an effective remedy European Charter of Human Rights (ECHR) Article 8: Right to respect for private life and family life Article 14: Prohibition of discrimination Charter of Fundamental Rights of the European Union (CFR) Article 7: Right to respect for private and family life Applicable EU laws, regulations and directives regarding Human Rights Human Rights Treaty on European Union (TEU) Article 4: Processing data carried out by national intelligence and military agencies falls outside EU law Treaty on Functioning of the European Union (TFEU) Article 16: Legal basis of protection of personal data Applicable EU laws, regulations and directives regarding Data Protection Data Protection Regulation 2017/2226 Established an Entry/Exit System (EES) to register entry and exit data and refusal of entry data of third-country national crossing external boarders of Member States Determined the conditions for access to the EES for law enforcement purposes Applicable EU laws, regulations and directives regarding Border Control Border Control Scope & limitations of fundamental rights as applied to use of FRT (for national security, border control) Use of FRT: Compliance-Non-compliance with EU HR Law Private and public sector obligations Challenges, gaps, opportunities Analysis and Conclusion Analysis and conclusion Main stakeholders: Amsterdam Schiphol Airport Royal Netherlands Marechaussee (KMar) Cathay Pacific Vision Box Introduction Introduction Main points: The program's goal is the development of self-boarding technology, by which the passengers will be able to pass through the Schiphol checkpoints by facial recognition Procedure Regulation Schiphol Airport case study Treaty on European Union (TEU) Main aspects: Human Rights Data Protection Border Control Other relevant principles: Respect for private life and protection of personal data Non-discrimination Rights of the child and of elderly people Freedom of expression and freedom of assembly and of association Right to good administration Right to an effective remedy ECHR - European Charter of Human rights Article 8: Right to respect for private life and family life Article 14: Prohibition of discrimination CFR - Charter of Fundamental Rights of the European Union Article 7: Right to respect for private and family life Applicable EU laws, regulations and directives regarding Human Rights Human Rights GDPR - General Data Protection Regulation Article 4: "Biometric Data'' Article 5: Principles relating to the processing of personal data Article 6: Lawfulness of processing Article 9: Processing of Biometric Data Article 22: Automated individual decision-making LED - Law Enforcement Directives 2016/680 Article 3 and 10 (same as in GDPR) Regulation 2018/1725 TEU - Treaty on European Union ARTICLE 4: Processing data carried out by national intelligence and military agencies falls outside EU law TFEU - Treaty on Functioning of European Union Article 16: Legal basis of protection of personal data Applicable EU laws, regulations and directives regarding Data Protection Data Protection Regulation 2017/2226 Established an Entry/Exit System (EES) to register entry and exit data and refusal of entry data of third-country national crossing external boarders of Member States Determined the conditions for access to the EES for law enforcement purposes Applicable EU laws, regulations and directives regarding Border Control Border Control

Big Data Presentation

Transcript: After Sales Conference Big Data projects Mahir Suleymaov 09.IX.2018 What is Big Data? What is Big Data? Big Data is a term that describes the large volume of data... it is a natural resource.. and it affects our life everywhere Data everywhere... Data everywhere... However, it is easy to collect, hard to use.. when we use internet, phone, car and any gadgets - each single information, which we receive and present is a data Data is a weapon of XXI century. In today’s hyper-connected world data is often touted as a competitive advantage.. and it is a strategic privilege for decision-making. If you want to be one step ahead than your competitors, then you must insight the data! Why is it so important? Why is it so important? Big Data analytic is the process of examining large and varied data sets Big Data analytic is the process of examining large and varied data sets i.e., - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. i.e., - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. The differences between big data and analytics are a matter of: 1. volume 2. velocity 3. variety The differences between big data and analytics are a matter of: 1. volume 2. velocity 3. variety Real-time information makes Big Data possible for a company to be much more agile than its competitors. You cannot manage what you cannot measure... Impacts on Business Our Team Our Team Name qualifications/experience Name qualifications/experience Name qualifications/experience Our Clients Our Clients Project Overview Implication of Big Data to the automotive industry Objectives Customer Churn 1. 2. 3. Customer Lifetime Value Customer Targeting Strategy Strategy Deliverable 1 Deliverable 1 Deliverable 2 Deliverable 2 Deliverable 3 Deliverable 3 Next steps Next steps Timeline Timeline Stage 1 Stage 2 Stage 3 Time Pricing Pricing Offer 1 Offer 2 Offer 3 $1,000 $2,000 $3,000 Service 1 Service 2 Service 3 Service 4 Service 1 Service 2 Service 3 Service 4 Service 1 Service 2 Service 3 Service 4

Big Data Presentation

Transcript: EVALUATING BIG DATA's APPLICATION TO REGIONAL CENTRAL BANKS A little about me... 18 years in Information Technology B.Sc. in Computer Science; Current interest: building web applications using Node.js and angular2 Future plans: M.Sc. in IT/DataScience discipline Personal Life: I enjoy the beach life, singing, working out, liming with friends and most of all working with the youth of my church in the community In the last week I also became an uncle A little about me... Ross Simmons Analyst/Programmer Central Bank of Barbados EVALUATING BIG DATA's APPLICATION TO SMALL REGIONAL CENTRAL BANKS “Big Data will become the key basis of competition, underpinning new waves of productivity and growth, innovation, and consumer surplus as long as the right policies and enablers are in place” - (McKinsey 2011). Quote: Introduction What is your presentation about? Introduction Make it clear to the audience! Who Are You? PROJECT OVERVIEW Are you selling something or presenting a personal project? Personal or Business? Add Images or Videos PRODUCTS & SERVICES What makes your presentation special? Present the Details Add as many slides as you need. Make Your Point CONCLUSION & QUESTIONS What? Why? When? Who? Question Time CONTACT INFORMATION How can people reach you? Contact Information Create your own layout and change colors Customize the Design Create your own layout and change colors Customize the Design Customize the Design Big Data “Data is the new Oil. Data is just like crude. It’s valuable, but if unrefined it cannot really be used” – Clive Humby, HumbyandDunn. Big Data

Big Data Presentation

Transcript: Digital Marketing Strategy for Digital Video Commercial The use of local country census and demographic data designed to identify and reach new retail prospects. We can target where the best prospects live across Africa Overlay where they live, with the best accessible retail locations in the prospects geographic footprint Seen as an archaic brand Low top of mind awareness for Philips. Mistaken for other Phillips Brands (Phillips Consulting, Phillips Engineering, Phillips Petroleum) especially among the younger demographic. Outcome: Awareness & Participation Target Audience Size 1,000,000+ Source: Social Baker Government – Ministries, Government Agencies Every good conversation starts with good listening. Google display ads Technology Trends Port Harcourt Twitter impressions Our role as digital marketers, is to navigate Philips’s aggressive reentry into the West Africa marketplace by executing our robust digital messaging strategy using C.I.D.M. Interpreting this brand position from an emotional perspective into purchase action in the West African marketplace Enjoy quality and good design at a price Google Display Network, Facebook Ad, and LinkedIn Ad The mobile phone is fast becoming as much an African symbol. 71% of adults in Nigeria, 62% in Botswana and more than half the populations of Ghana and Kenya own a mobile phone. Africa is the world's fastest-growing mobile phone market. It's 600m users make it second only to Asia. Government/NGO officials City Focus - No Activity Philips has a great heritage dating back to 1891 and plays on the global stage Has a strong track record of creating quality innovative products The brand is synonymous with quality and reliability. Cosmopolitan, Urban elegant and classical Search Engine Optimization (Organic Search) Paid Search (PPC Keyword Buying) Nearly 20 percent of Lagosians are now members of Nigeria’s growing middle class. Creative execution Sales Targeting What do you call a bulb? (Campaign) 2. Commercials for Lighting 2. SEO = Monthly impressions Driving purchase consideration and positive attributes towards the Philips brand and products by consumers. Sophisticated health conscious lifestyles Abuja Current Online Activity we plan on doing this by: Facebook RATIONALE Frying, roasting, grilling and baking with the Philips Airfryer is possible with much less fat than the usual frying/ deep frying method. The varied mix of executions highlight these benefits. Most visited sites via Mobile internet Inform Philips is part of our community, communities are made up of people. People use Philips products. As such ... Target Audience Recreate awareness of the Philips brand Develop and implement digital assets/capabilities that will be the bedrock of a comprehensive digital marketing campaign for the company brand and business groups Define the Philips brand tonality and manner across various digital assets Build and nurture the Philips online consumer community Aforementioned objectives must results in actionable sales Sponsored Post The Lighting section provides the following information: 1. Guidance for target consumers to make the right CFL bulb choice for their purpose (as choosing one can be a confusing task from the multiple of options available. (one of the steps to choosing a bulb was displayed; the other steps being choose your bulb base, choose your light output and choose your light control) The Competition Target Audience Size 1,000,000+ We want to make users like and trust us. That means listening to what users have to say and having thoughtful conversations about things they care about. Connections are people and channel affiliations we collaborate with in order to make sure we’re reaching the right users in the right places. Retail sales strategy planning Marketing campaign planning Public relations strategy planning Media buying and placement Real estate planning and much more... Understanding of the West African (Nigeria/Ghana) Markets and Digital Landscape Mobile Data Penetration Rate Facebook Microsite Innovation Work Group Ideas 5. E-Commerce Target Audience Size 100,000+ Source: Social Baker 6 Mobile internet users account for 60.69% of the Nigerian Internet population while 30.31% surf the internet using Desktops. Mobile penetration has been largely responsible for the accelerated growth in internet subscribers Search Engine Optimization (Organic Search) Paid Search (PPC Keyword Buying) The joy of becoming a parent Knowing that all is well with the baby The confidence that comes with a better diagnosis 3 Billion CFL Campaign Lighting $ 3. A demonstration of what lighting can do for various businesses for their walls, ceilings and outdoor (demos have been included for some businesses; the demos are positional and not the actual lighting options for these various spaces) Takoradi An average Nigerian spends 3hours surfing the internet daily - Low Activity Facebook Ad Upper middle and upper social economic class Consumer Insight + SMP Benefit

Big Data Presentation

Transcript: Available Mobile Phone Options “Visualization clearly has an important role to play in enabling residents to understand and manage their energy use because providing feedback on such use can encourage conversation.” aggregate power history real time aggregated power limited visual analytics Fixed Income Households The Eco-friendly Can Energy Solutions be Achieved Through Visualization and Big Data? Build effective narratives of current energy usage Current Feedback and Energy Reporting in BC "Aesthetics. The purpose of information visualization is the insights into data that it provides, not just pretty pictures. But what makes a picture pretty? What can we learn from making a pretty picture and enhancing the representation of insights? It’s important, therefore, to understand how insights and aesthetics interact, and these two goals could sustain insightful and visually appealing information visualization.'' -Chaomei Chen Unsolved Problems Energy Feedback Options Under Development Hot new area for energy monitoring Two start ups in California: Plotwatt & Bidgely Bidgely has raised $16 Million for energy disaggregation applications (November 2nd 2015) What We Want to Accomplish Goal: design an evocative record of the usage of energy through time To create awareness about personal energy consumption while promoting sustainable and realistic change by developing an application that is both easy to comprehend and visually appealing. Households BC Hydro Architects/Realtors/Investors Municipalities Stakeholders Platforms Energy Disaggregation enhanced monthly bills mobile apps online dash boards specialized in-home devices embedded with ambient displays Optimizing Home Energy Usage Using Big Data - Dr. Lyn Bartram, Design Challenges and Opportunities for Eco-Feedback in the Home p.52, 2015 Abhisekh Patra | Alyssa Fraser Conrad Schwab | Katharine Colclough Mandy Nilson Approach "Energy is still largely incomprehensible to millions of residents, and this is a prime cause of much waste." Users Affective Engagement with Interactive Visualizations Inspiration Denotation vs. Connotation Questions? - Dr. Lyn Bartram, Design Challenges and Opportunities for Eco-Feedback in the Home p.52, 2015

Big Data Presentation

Transcript: A Big Data Presentation C B - Amal Bazilah (19b3110) - Amal Ummi Naqibah (19b3083) - Batrisyia Safwah (19b3108) Topic: Financial Aid (Monthly Welfare Assistance) -Siti Zahidah (19b3113) Introduction 1) Many people applied for the Monthly Welfare Assistance : - Receive more than they genuinely require (dependency) - Receive less/ insufficient financial support for their necessities Problems : Background 2) Difficulty in applying for some people (tedious & time consuming) 3) Dishonesty in presenting relevant documents & living condition Provided by? - Jabatan Pembangunan Masyarakat ( Department of Community Development) JAPEM "Help alleviate the burden of an individual or family who are living in difficulty and helplessness" Improvement needed in assessing: 1) Expenses 2) Number of children 3) Minimum living conditions (Achieved?) 4) Income 5) Application system How application currently works: Submission of letter to director of JAPEM or village heads; directly visit the headquarters Documents should be included with the letter (such as...) JAPEM Jabatan Pembangunan Masyarakat; department of Community Development under ministry of culture youth & sports The need for big data To improve the efficiency of the system To improve the efficiency of the system Current system: 1) Monthly investigation is done on the recipients to ensure the extend of which they are eligible Based on: -Having no income -Difficulty in living and the number of children who are still in school Reduction / Termination of payment to recipients: -Married or working. -Wife is working and is considered to be able to help in every day living. -Received assistance from government agencies or non-governmental agencies. -Means of livelihood that can support their families. -Numerical data - taken via different database from the government & private sector e.g records and data phone number. -The data - made by both human and machine, generated and depend on a data model. -Sources data is collected from - SQL databases, online forms, sensors (GPS), Network and Web server logs and medical devices. Structural data Type of big data needed -It is easily recorded, accessed and stored -More effective processing and analysis -Data structure is well defined and data can be easily updated or deleted -Data mining is made easier -Ensuring security to data is easier Why it is used? Advantages -In the past, due to limited storage and the cost, it is collected using relational databases and spreadsheets to effectively manage data. -It is now often managed using SQL (Structured Query Language) as it is quick and efficient. How it is collected? Methods Where & how big data will be collected Application: 1) Personal Information are inserted by trusted employees in the respective departments/ministries 2) Income of the parents ( from employers) 3) Minimum expenses that each family/ family members require. Source of info Information are derived from various sources - big data How will the data be analysed? - Data such as the minimum monthly expense of each family member is collected, estimated and compiled together. - The system will automatically calculate the total needs and requirements of the family - Any family with living conditions that requires the greatest care will be prioritized Family member - The minimum quantity of food needed for each member (minimum calories needed based on their BMI and BMR) - School expenses for each child (books, stationeries, uniform, school fees) - medical needs (unprovided medicines) - Special needs (wheelchairs, therapy products, assistive technology) Whole family Car fuel House bills: - Water bills -Electricity bills -Groceries Expected results A more confidential, secure & reliable system of financial tracking and personal data, (for the process of financial aid) Comparison Expected results /improvement Example Of

Big Data Presentation

Transcript: BIG DATA Humanistic Perspective on Data Case Study: Who Uses Big Data? Marketing Target interests Intelligence Gathering Profiling Product Improvement Feedback The 3 V's of Big Data Alexis Gregerson, Roshni Changela, Michael McKeirnan, Sean Dolan, Sanjay Sagar, Sun Kim http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&docid=34uDaDViB81vTM&tbnid=1hpymMnLVe05pM:&ved=0CAUQjRw&url=http%3A%2F%2Fwww.saldef.org%2Fnews%2F7872%2Fattachment%2Fcomcast-logo%2F&ei=TsUKU7m9Es66oQTJgoGAAg&bvm=bv.61725948,d.cGU&psig=AFQjCNFLGv4hckLYRETjtxxyKBXawGSbag&ust=1393301189739839 Find the interactive heat map here: http://mckeimic.com/info What does Big Data Mean for you? Infographics Display vast amounts of data Benefits Engage consumers Allow new discoveries Risks Potentially misleading Can lead to false discoveries Big data is being monitored for potential threats Uses Accumulo to "tag data" Noise is coming faster than the Signal Success rate is low Is our invasion of privacy worth it? How Big is Big Data? Lecture Group 17: What is Big Data used for? Washington Voter Registration Healthcare: 20% decrease in patient mortality by analyzing streaming patient data Telco: 92% decrease in processing time by analyzing networking and call data Utilities: 99% improved accuracy in placing power generation resources by analyzing 2.8 petabytes of untapped data -(IBM) http://www.economist.com/node/15557443 http://whatis.techtarget.com/definition/3Vs http://www-01.ibm.com/software/data/bigdata/industry.html http://www.oxforddictionaries.com/us/definition/american_english/infographic http://www.fastcodesign.com/1669222/a-case-study-in-how-infographics-can-bend-the-truth http://www.healthcarecommunication.com/Main/Articles/7_common_problems_with_infographics_9536.aspx http://www.healthcarecommunication.com/Main/Articles/7_common_problems_with_infographics_9536.aspx http://www.nytimes.com/2011/04/03/business/03stream.html?_r=3& http://www.google.com/imgres?client=safari&rls=en&biw=1129&bih=538&tbm=isch&tbnid=Oi0dU87Q224zwM%3A&imgrefurl=http%3A%2F%2Fsac.unm.edu%2F&docid=BbGU6Scehn4xOM&imgurl=http%3A%2F%2Fsac.unm.edu%2Fimages%2Flongtermfiles%2Ffacebook_logo.jpg&w=2197&h=1463&ei=E8QKU-SaKI3roATw54KYAg&zoom=1&ved=0CGcQhBwwAA&iact=rc&dur=567&page=1&start=0&ndsp=8 http://ron-tornambe.bunkerhill.com/images/clients/ibm-logo.png Closing So is it working? Silicon Valley (Twitter feed??) Summary NSA "Data will be the next natural resource" -Ginni Rometty, IBM CEO BIG DATA: WORKS CITED What comes to mind when you hear big data? A collection of most often large and complex data sets Difficult to process using traditional data processing systems and applications Interviews here Example: Correct Numbers Represented NOW Bag gives user impression that debt has quadrupled in size

Big Data Presentation

Transcript: Suggestions and Ideas to improve existing model Exposure Apart from Curicullum Exposure Apart from Curicullum More Indusrial Visits More Indusrial Visits More Industrial visits should be organised to the core compani... More Industrial visits should be organised to the core companies of particular specialisations such as Mu Sigma (Big Data) so that the students could get more exposure of the Corporate sector and could better understand the practical and live working of their specialisation companies. Seminars Except the Technical Training Seminars Except the Technical Training Expert Practical Sessions on various technologies . More hands on experience More knowledge on Who an Industry Works .i.e.An inside view of a corporate TIMELINE TIMELINE 2017 MAP MAP CHART Label 1 Label 2 Label 3 Label 4 CHART More Help in Placements More Help in Placements Conduct Mock INterviews and GD's Conduct Mock INterviews and GD's Internship in IBM Internship in IBM Internship in IBM should be provided to IBM Specialised Students in their specific Specialisations Our SGPA less than CSE Our SGPA less than CSE Due to less number of students ,Students of IBM-C... Due to less number of students ,Students of IBM-CSE have lesser CGPA than CSE Students . So,Eligibilty Criteria for CSE and CSE -IBM should differ and should not be o the basis of CGPA. Change in IBM Resources Change in IBM Resources Study Material to be changed Study Material to be changed The IBM Study material is not up to the mark. The Other reference books are more useful than IBM Books. The IBM Study material just contains the Presentations with some Explanation and are very less useful. Specialised LAbs Required Specialised LAbs Required More Labs required with systems having more than 8 GB RAM . Labs with Specialised Softwares for Each Specialisation . As of now,We have only one lab with Systems having 8GB RAM and Many IBM Tools require 8 GB RAM. Engineering Practice Engineering Practice *Since,the test is just of 1 hour and EP lab has two lectures .So,we have to sit idle for one lecture. *EP should be removed from the curicullum as it isn't benifitting us . *If,removing isn't possible,then reduce it to one lecture so that we could do something Productive. Other KEY POINTS Other KEY POINTS *Transport Facilities for day scholars after TPP extra classes. *Library of Block-9 should be available till 8 pm and should include books of our specialisations. *Inter departmental Sports meet should be promoted and Some Fun Activities should also be conducted. Some Free Lectures Some Free Lectures *Some Free lectures should be introduced in our time table (ATLEAST ONE DAY) ,because our Time Table is jam-packed and we have no free time to visit other teachers or departments .

Now you can make any subject more engaging and memorable