More Related Content


Recently uploaded(20)


Big data

  2. AGENDA SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY | IST 659 What is Big Data? The 3 V’s of Big Data Advantages and disadvantages of Big Data Big Data challenges Big Data applications
  3. WHAT IS BIG DATA ? SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY | IST 659 TERM BIG DATA Big data is a term that describes the large volume of data from traditional and digital sources inside and outside a company that represents a source for ongoing discovery and analysis • both structured and unstructured • Inundates a business on a day-to-day basis
  4. 3 V’S OF BIG DATA While the term “big data” is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old. Big Data gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three Vs  Volume  Velocity  Variety 4 SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY | IST 659
  5. VELOCITY  The data growth and social media explosion have changed how we look at the data. There was a time when we used to believe that data of yesterday is recent. But today, the data movement is now almost real time and the update window has reduced to fractions of the seconds.  RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.  Velocity refers to the speed of information generated and flowing into the enterprise  Every big data analytics project will ingest, correlate and analyse the data sources, and then render an answer or result based on an overarching query. 5 SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY | IST 659
  6. VOLUME  Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to- machine data.  It is very common to have Terabytes and Petabytes of the storage system for enterprises. As the database grows the applications and architecture built to support the data needs to be revaluated quite often.  Sometimes the same data is re-evaluated with multiple angles and even though the original data is the same the new found intelligence creates explosion of the data.  In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have made the process easy. 6 SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY | IST 659
  7. VARIETY  Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.  It is the need of the organization to arrange it and make it meaningful. It will be easy to do so if we have data in the same format, however it is not the case most of the time. SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY 7
  8. MORE ON BIG DATA The Big Data landscape is dominated by two classes of technology: 1. Systems that provide operational capabilities for real-time, interactive workloads where data is primarily captured and stored 2. Systems that provide analytical capabilities for retrospective, complex analysis that may touch most or all of the data. Each has driven the creation of new technology architectures. Operational systems, such as the NoSQL databases, focus on servicing highly concurrent requests. Analytical systems, on the other hand, tend to focus on high throughput; SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY 8
  9. ADVANTAGE OF BIG DATA SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY 9  Improved Customer Insights (For Ex. Southwest Airlines, extracts Large volume of data from interactions between customers and personnel to get a better understanding of their customers.)  Faster, better decision making (Ex. Caesars, a leading gaming company that has long embraced analytics, is now embracing big data analytics for faster decisions.)  Cost Reduction (Big data technologies like Hadoop and cloud-based analytics can provide substantial cost advantages.)  New products and services (Ex: GE, for example, has made a major investment in new service models for its industrial products using big data analytics.)
  10. DISADVANTAGE OF BIG DATA  It requires special computer power  Using real-time insights requires a different way of working within your organisation  Difficult to assess accuracy and uncertainty  Privacy and confidentiality issues SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY 10
  11. BIG DATA CHALLENGES  Capturing data  Storage  Searching  Sharing  Transfer  Analysis  Presentation SCHOOL OF INFORMATION STUDIES | SYRACUSE UNIVERSITY 11