CBSE open book exam plan evokes mixed reactions.
Students will be forced to think beyond narrow definitions of what they learn from books, making learning more experiential.
Rote learning a closed chapter, CBSE to begin open book era.
Teachers brace for open book challenge.
Open Book Exam System by CBSE
Sometime back there was a news that CBSE is planning to introduce Open Book Exam system for the current session "CBSE is all set to introduce the “OPEN BOOK EXAM “ for classes IX, X, XI in 2013 -2014 session and in Class XII from next academic session, reports some section of the media"
The Video and the Post here explains what exactly is an Open Book Exam
Some Facts about the Open Book Exam System
Open book tests are not easy tests.
Open book tests teach you how to find information when you need it.
The questions are designed to teach you how to use your brain
The CBSE open book system will be for 15-20% of the marks. The schools will be supplied with the text material in few months before the commencement of Summative Assessment – 2. (It will start from 2014).
CBSE open book exam plan evokes mixed reactions.
Students will be forced to think beyond narrow definitions of what they learn from books, making learning more experiential.
Rote learning a closed chapter, CBSE to begin open book era.
Teachers brace for open book challenge.
Open Book Exam System by CBSE
Sometime back there was a news that CBSE is planning to introduce Open Book Exam system for the current session "CBSE is all set to introduce the “OPEN BOOK EXAM “ for classes IX, X, XI in 2013 -2014 session and in Class XII from next academic session, reports some section of the media"
The Video and the Post here explains what exactly is an Open Book Exam
Some Facts about the Open Book Exam System
Open book tests are not easy tests.
Open book tests teach you how to find information when you need it.
The questions are designed to teach you how to use your brain
The CBSE open book system will be for 15-20% of the marks. The schools will be supplied with the text material in few months before the commencement of Summative Assessment – 2. (It will start from 2014).
Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Dri...Adam Thierer
"Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Driven Innovation." A presentation by Adam Thierer (Mercatus Center at George Mason University) made on September 11, 2014 at AEI-FCC Conference on "Regulating the Evolving Broadband Ecosystem."
This year we have reached the stage where 50% of the world’s population is connected to the Internet, compared to 40% in 2016. And, with more people online than ever before, every minute that goes by witnesses 3.5 million Google search queries, $751,522 spent, 156 million emails sent, 342,000 apps downloaded in mobile app stores and 46,200 posts uploaded to Instagram.
Age Friendly Economy - Legislation and Ethics of Data UseAgeFriendlyEconomy
Upon completion of this module you will:
- Be able to recognize the necessity of regulating big data
- Understand the difference between privacy and data protection
- Know how to implement actions of data protection into your own (future) company
Duration of the module: approximately 1 – 2 hours
eMarketer Webinar: Perspectives on Digital Privacy—Marketers, Consumers, FedseMarketer
Join eMarketer Principal Analyst David Hallerman as he helps companies involved in the digital ad space figure out the best questions to ask and next steps to take to address digital privacy.
It has been said that Mobiles +Cloud + Social + Big Data = Better Run The World. IBM has invested over $20 billion since 2005 to grow its analytics business, many companies will invest more than $120 billion by 2015 on analytics, hardware, software and services critical in almost every industry like ; Healthcare, media, sports, finance, government, etc.
It has been estimated that there is a shortage of 140,000 – 190,000 people with deep analytical skills to fill the demand of jobs in the U.S. by 2018.
Decoding the human genome originally took 10 years to process; now it can be achieved in one week with the power of Analytic and BI (Business Intelligence). This lecture’s Key Messages is that Analytics provide a competitive edge to individuals , companies and institutions and that Analytics and BI are often critical to the success of any organization.
Methodology used is to teach analytic techniques through real world examples and real data with this goal to convince audience of the Analytics Edge and power of BI, and inspire them to use analytics and BI in their career and their life.
The presentatio offers an overview on big data in/for global development - i.e. how big data & data science are being developed in emerging and developing regions.
It is divided in three main sections:
(1) what is big data (as of today) & what is big data in/for development?
(2) Who is actually doing «big data for development»? Who are the main intrnational actors/stakeholders? What are main experiences?
(3) Why are we doing this? - i.e. are we doing this right? What are the main access, capacity / interpretation / ethical issues?
IoT & Big Data - A privacy-oriented view of the futureFacundo Mauricio
Understanding the future based on the current technology, with a focus on Big Data and Internet of Things (IoT). A discussion of privacy and personal information and how it affects us.
Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Dri...Adam Thierer
"Internet of Things & Wearable Technology: Unlocking the Next Wave of Data-Driven Innovation." A presentation by Adam Thierer (Mercatus Center at George Mason University) made on September 11, 2014 at AEI-FCC Conference on "Regulating the Evolving Broadband Ecosystem."
This year we have reached the stage where 50% of the world’s population is connected to the Internet, compared to 40% in 2016. And, with more people online than ever before, every minute that goes by witnesses 3.5 million Google search queries, $751,522 spent, 156 million emails sent, 342,000 apps downloaded in mobile app stores and 46,200 posts uploaded to Instagram.
Age Friendly Economy - Legislation and Ethics of Data UseAgeFriendlyEconomy
Upon completion of this module you will:
- Be able to recognize the necessity of regulating big data
- Understand the difference between privacy and data protection
- Know how to implement actions of data protection into your own (future) company
Duration of the module: approximately 1 – 2 hours
eMarketer Webinar: Perspectives on Digital Privacy—Marketers, Consumers, FedseMarketer
Join eMarketer Principal Analyst David Hallerman as he helps companies involved in the digital ad space figure out the best questions to ask and next steps to take to address digital privacy.
It has been said that Mobiles +Cloud + Social + Big Data = Better Run The World. IBM has invested over $20 billion since 2005 to grow its analytics business, many companies will invest more than $120 billion by 2015 on analytics, hardware, software and services critical in almost every industry like ; Healthcare, media, sports, finance, government, etc.
It has been estimated that there is a shortage of 140,000 – 190,000 people with deep analytical skills to fill the demand of jobs in the U.S. by 2018.
Decoding the human genome originally took 10 years to process; now it can be achieved in one week with the power of Analytic and BI (Business Intelligence). This lecture’s Key Messages is that Analytics provide a competitive edge to individuals , companies and institutions and that Analytics and BI are often critical to the success of any organization.
Methodology used is to teach analytic techniques through real world examples and real data with this goal to convince audience of the Analytics Edge and power of BI, and inspire them to use analytics and BI in their career and their life.
The presentatio offers an overview on big data in/for global development - i.e. how big data & data science are being developed in emerging and developing regions.
It is divided in three main sections:
(1) what is big data (as of today) & what is big data in/for development?
(2) Who is actually doing «big data for development»? Who are the main intrnational actors/stakeholders? What are main experiences?
(3) Why are we doing this? - i.e. are we doing this right? What are the main access, capacity / interpretation / ethical issues?
IoT & Big Data - A privacy-oriented view of the futureFacundo Mauricio
Understanding the future based on the current technology, with a focus on Big Data and Internet of Things (IoT). A discussion of privacy and personal information and how it affects us.
Abstract:
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
A keynote presentation about data privacy and policy, and the ways leading retailers use data and advanced analytics to humanize and personalize consumer experiences of their brand.
According to Gartner, Big Data will be the next “disruptive technology” and will transform customer relationship management industry.The possibilities that Big Data offers are endless but companies first need to invest in CRM software
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
1. Big Data and You
The How & Where. The Advantages & Dangers. The Questions…
2. Let’s Take A Look
• Big Data: What is it?
• How big is Big Data?
• How and where is it collected?
• Where is it stored and is it stored safely?
• Your Permission to collect your data
• Advantages for businesses and our daily lives
• Possible dangers and risks associated with big data
• What can you do?
• Contemplation and questions
4. Wikipedia Definition
• Big data is the term for a collection of data sets so large
and complex that it becomes difficult to process using on-hand
database management tools or traditional data
processing applications.
5. It’s Bigger Than Ever
• Traditionally, data was structured and neatly organised in databases
• Post-internet, a proliferation of ‘unstructured data’ is generated by everything
we do online
• Globally, the number of gadgets that can record and transmit data –
smartphones, smart fridges, CCTV cameras and digital sensors- has exploded and
along with it, the volume of data produced
• 90% of all the data in the world today has been created in the past few years
• 2.5 exabytes - 2.5 billion GB - of data was created every day in 2012 (IBM)
• We now need new tools and approaches to understand and use these huge and
complex data sets
7. Collection: Social Media
• Average global internet user spends 2.5 hours on social
media every day
• We reveal a lot about our interests, dislikes, relationships,
travel and careers
• We get more personalized content and targeted advertising
• Facebook’s ‘Like button’ is clicked 2.7 billion times a day (BI)
• 22% of LinkedIn users have between 500-999 first-degree
connections (BI)
• Twitter processes approximately 143,199 tweets per second
worldwide (BI)
• Millions of product images are pinned to boards on Pinterest
every day
8. Collection: Consumer Data
• Credit card use and retail transactions = every time
you swipe a card
• Loyalty cards
• Acxiom’s servers process more than 50 trillion data
transactions per year and their database contains
info on 500 million consumers worldwide – 1,500
data points per person
• Sending an email (Gmail’s email scanning for
targeted marketing)
• Going on vacation
• Completing a survey
• Google, Yahoo and Bing (search engines)
9. Collection: ‘Quantified Self’ apps
• Nike+ Fuel Band
• Fitbit
• Jawbone’s UP band
• Weight and body
measurements
• Heart rate, blood pressure and
glucose levels
• Location, duration and speed of
exercise activity
10. Where Is It Stored? The Cloud.
• In the simplest terms, cloud computing means storing and accessing data and
programs over the Internet instead of your computer's hard drive. (PC Mag)
11. Did Anyone Ask You?
• In Rio de Janeiro, IBM and the Brazilian government have teamed up to create a
central surveillance hub for the 2014 World Cup
• On Facebook, Twitter, Instagram, Gmail, etc, you probably clicked, ‘Agree’, for
the terms and conditions without reading them entirely
• In Boston, citizens have complained about their privacy over the use of licence
plate recognition software
• In Greece, the government uses Google Earth to search for undocumented
swimming pools and then matches that against tax records to find tax offenders.
They have found 16, 974.
• The NY Times has reported that retail stores gather data of in-store shoppers’
behaviour and moods, their gender and how long they spend looking at products
before buying
13. Corporate Advantage
• 400 large companies that are already using big data
analytics “have gained a significant lead over the
rest of the corporate world” (Bain & Co report)
• Anyone who uses big data analytics can make their
manufacturing and production processes more
efficient (BBC News)
• Find hidden business trends
• Create better marketing campaigns
• Capture financial risk
• Analyse consumer buying behaviour
• Improve customer service
14. Employment – Data Scientist
• = A high-ranking professional with the training and curiosity to make discoveries
in the world of big data and then communicate them effectively to the business
and IT leaders so that the business can use those findings to solve business
challenges (BBC/IBM)
• 5 to 10 years ago, the job of a Data Scientist never existed and currently there is a
shortage of them
• Average Salary? $110, 000 USD (FastCompany)
• 4.4 million big data jobs by 2015 (McKinsey)
15. Weather Prediction and Services
• Satellites monitor global rainfall, helping
meteorologists use big data analytics to
predict storms around the world
• The Weather Company collects 20 terabytes
of data daily, serving hundreds of
thousands of customers: 30 airlines,
emergency services, shippers, utilities,
insurers and developers of many mobile
weather apps
• Farmers who analyse weather, soil,
topography and GPS tractor data can
increase their crop yields
16. Healthcare
• Predict which heart attack patients are at
risk of having a second heart attack
• ‘Magic Carpet’ patient monitoring for
seniors
• Stop the flu from spreading with apps like
FluNearYou
• Drug Information Systems (DIS) helping
doctors, pharmacies and hospitals track
which medications are dispensed and used
therefore reducing drug interactions
• Use of electronic information –patient
records, prescriptions, imaging, test
results –reduces the number of patient
visits to doctors, clinics, and hospitals
17. …and More…
• Understand traffic patterns via GPS data to improve taxi service, public
transportation, parking availability, traffic flow and fuel conservation
• Self-driving cars
• Home energy monitoring with appliances and utilities for more energy
conversation awareness and solutions
• Analyse sports and players to make predictions and increase winning
• Improve political campaigns
• Crime fighting and capturing criminals
19. High School and Your Unshakable Past
• Data is being collected on students to improve teaching methods, test scores and
to decrease drop-out rates
• What if this data collected never disappears and stays on a your academic record
permanently only to be retrieved by prospective employers?
• Academically tracking students can limit their opportunities in life when the data
suggest an educational track to pursue
• Australia’s largest telecomm: more than 25% of Australian bosses screened job
candidates based on their social media profiles
20. Ethics, Risks, Unknowns…
• Mark Zuckerberg, CEO of Facebook, promotes risk-taking as one of his company’s
core values but when they make mistakes, society bears the cost(s)
• There is potential danger from inappropriate disclosure of information and data
• More than ever before, individuals and groups can be profiled and therefore
manipulated
• Access to data could be restricted to those in power or to those able to pay
• An election could be significantly influenced: voters are shown certain messages
and not others based on data found in their emails, texts and social media posts
• Who controls the data and tools and where is the legislation and community
engagement?
21. The NSA ‘Bumblehive’
• The US National Security Agency’s huge data centre in Utah can store a
yottabyte of data = one thousand trillion GB
22. Oh Yes, The NSA
• Secrecy prevented checks and balances on its
activity and therefore it has ignored the privacy
rights of hundreds of millions of people
• The NSA collects up to 5 billion cell-phone
location records per day, worldwide without a
warrant or court order (the Post)
• The NSA’s Co-Traveler analytics tool for
cellphone location data can make you suspicious
because of where you have been AND whom
you have been near
• The NSA has been recording ALL of one foreign
country’s phone calls, then listening to those
conversations up to a month later (the Post)
24. Not Into Being Tracked?
• Pay only in cash
• Give up your loyalty cards
• Stop using coupons
• Abandon social media
• Write letters instead of emails
• Stop using text messages to communicate
• Don’t make any phone calls
• Stay in one location or turn off your GPS
• Shop in stores and not online (oh wait, stores
monitor you, too…)
• Don’t use Skype to call home or friends
25. But, I’m Not Doing Anything Wrong!
• Is your definition of ‘wrong’ the same as the government’s?
26. Now That You’re Scared, Let’s Review!
• Big Data: What is it? = too large, too complex
• How big is Big Data? = 2.5 billion GB of data was created daily in 2012 (IBM)
• How and where is it collected? = social media, consumer data, ‘Quanifiable Self’
• Where is it stored and is it stored safely? = the Cloud (Where’s that?!)
• Your Permission to collect your data = Have you been asked?
• Advantages for businesses and our daily lives = corporate, data scientist,
healthcare, weather, crime
• Possible dangers and risks associated with big data = high school, employability,
NSA, elections
• What can you do? = Live in a log cabin in the forest
28. You’re Supplying the Data
• How do you feel about so many data points being collected about you?
• How do you know that your data is being stored in a safe, protected place?
• What types of data don’t you want to share?
• Why don’t you read the Terms and Agreements before you click, ‘Agree’?
Before starting: How many of you use at least 3 social media apps like Facebook, Twitter, Yelp, Pinterest, LinkedIn, etc?
How many of you own a smartphone? A tablet?
How many of you use a free email service like Gmail, Hotmail or Yahoo?
How many of you use Skype or Google Hangouts to make calls and video chats?
Is there anyone here who never uses the Google search engine?
Online: : email, online shopping, text messages, tweets, Facebook posts and YouTube videos
Facebook: shows what we care about
LinkedIn: helps understand recruitment and employee retention
Twitter: shows in real-time what news and information people care about
Pinterest: shows the aspirations of millions of shoppers
-Magic carpet: monitor the activity of seniors by using sensors in the carpet and senses abnormalities and sends an alert to family or caregivers
-FluNearYou: surverys users to monitor possible symptoms and flu activity in a region