Big Data and Impact of Data Analytics


Big Data and Impact of Data Analytics

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  1. Big Data and Impact of            Data Analytics

    Slide 1 - Big Data and Impact of Data Analytics

    • By
    • Naveen Reddy Thumma
    • y00749755
  2. What is Big Data ?

    Slide 2 - What is Big Data ?

    • Big Data a term which is now popular amongst business circle as it is used to make their business organisations more profitable, reliable and help them build good customer support
    • The term 'Big Data' appeared for first time in 1998 in a Silicon Graphics (SGI) slide deck by John Mashey with the title "Big Data and the Next Wave of InfraStress
    • Big Data is not only used by some business organisations but it used by government to help citizens to overcome challenges like health care, job creation and natural disasters
  3. Data collection for Big Data Analytics

    Slide 3 - Data collection for Big Data Analytics

    • The data for bid data analytics is collected from all sorts of sources as an unstructured data and analysed using big data techniques .
    • Major amount of this data is generated from web this type
    • became more popular after introducing social networking sites
    • The data is also collected internally from an organisation
    • and stored and used for future analysis purpose .
    • The data that is collected for data analysis is different in many dimensions like
    • Volume
    • Velocity
    • Variety
    • Veracity
  4. How Data Analytics is used in different                      fields and business

    Slide 4 - How Data Analytics is used in different fields and business

  5. Data analysis in business

    Slide 5 - Data analysis in business

    • In terms of business world to set the goals and achieve cost benefit analysis To bring best data analytic practices when confronted with massive data sets, big data came into picture in the business world
    • There is revolution in terms of data analytics in order to take the quality decision making
    • It is estimated that enterprise servers processed 9.57 zettabytes of data globally in 2008, an amount equivalent to nearly six gigabytes of data daily for every person in the world
    • Big data is used by business organisations for decision making purpose,
    • Decision making is done by analysing a huge amount of data that is stored in organisation which is collected from all sources in organisation and this analysis is done in such a manner that it analyses each and every data sets that are present in companies data base and help take decisions according to this analysis summery.
  6. Data analysis In the process of Advanced Manufacturing

    Slide 6 - Data analysis In the process of Advanced Manufacturing

    • Advance Manufacturing is in the one where the complex production processes takes place
    • which generates a large amount of production data. It also mainly concentrates on Scalability and performance
    • There is gap observed between the analyst and manufacturer which is described in terms of 3 terms
    • 1) Capacity - what the data looks like
    • 2) Capability - How the data can be utilized
    • 3)Knowledge - How to perform knowledge
    • discovery and management
  7.         Data analysis by government                     organisations

    Slide 7 - Data analysis by government organisations

    • Big Data analysis is also used by government organisations to provide good governance to the
    • citizens by proving all that people are required to get by analysing the data from web and social media platforms and take decisions according to the requirements of citizens of country
    • Government uses big data to ensure that every one gets the benefits from government
    • Reduced social benefit overpayments
    • Proactively detected & deterred fraud and abuse
    • Reduced analysis time and improved efficiency
    • Improved program integrity and preservation of limited budgets for eligible citizens
  8. Data analysis In Crime Investigation

    Slide 8 - Data analysis In Crime Investigation

    • Crime solving and prevention had become the major challenges to the society and its
    • becoming more and more complex and requires a new approach
    • Data Analysis in crime investigation is used as
    • Deeper understanding of persons of interest, crime and incident patterns, location-based threats, etc. in order to predict and prevent crime
    • Improved case clearance rates
    • Stronger inter- and intra-agency collaboration
    • Faster, better informed response
  9. Data analysis in science and technology

    Slide 9 - Data analysis in science and technology

    • Big Data is also used in the fields of science and technology to analyse the large amount of data that is available, this analysis helps in research perspective for choosing appropriate technique to solve a problem that arises while researching
    • Medical Field:
    • The healthcare industry has generated large amounts of data, driven by record keeping, compliance and regulatory requirements, and patient care.
    • This data includes functions such as clinical decision support, disease surveillance, and population health management.
  10. Medical records and ICU data.

    Slide 10 - Medical records and ICU data.

    • Big data plays a major role in the field of medical science
    • Potential benefits include detecting diseases at earlier stages when they can be treated more easily and effectively
    • Managing specific individual and population health and detecting
    • health care fraud more quickly and efficiently
    • Data mining enables to characterize patient activities
    • to see incoming office visits.
    • Data mining helps identify the patterns of successful medical
    • therapies for different illnesses
  11. Weather forecasting

    Slide 11 - Weather forecasting

    • The Community Atmosphere Model and the Whole Atmosphere Community Climate Model ,
    • which are the Ensemble climate simulation model for Earth atmosphere model,
    • integrates the results executed in parallel repeatedly by the multiple number of members
    • On the other hand, the input and output files for climate simulation uses in binary type .This process the forecasts the atmospheric conditions after 100 years by using of multi-initial condition Ensemble simulation
  12. Major tools and frame works of big data

    Slide 12 - Major tools and frame works of big data

    • Apache Hadoop:
    • Apache Mahout:
    • Hive:
    • Pig and PigLatin:
    • Jaql:
    • Zookeeper:
    • Cassandra:
    • MOA(Massive Online Analysis)
    • SAMOA
    • Pegasus :
  13. Challenges Faced by Big Data Analytics

    Slide 13 - Challenges Faced by Big Data Analytics

    • Even though big data is popular it has many issues regarding privacy, data storage, accuracy
    • One of the most challenging issue of big data is privacy and security of big data repositories ,
    • This two topics are highly related to each other as analytics are often implemented in terms of data intensive procedures over distributed cloud nodes storing big data
    • in order to run such analytics against the data repositories data access is necessary
    • so for this we have to open the door to privacy and security breaches that effect the sensitive data
  14. Challenges Faced by Big Data Analytics

    Slide 14 - Challenges Faced by Big Data Analytics

    • Privacy for preserving social networking Data
    • Social networking data is the only most essential and reliable data that is used for real life big data
    • Social networking sites like Facebook and Twitter play’s the major role in this industry as large number of people are using these web sites every day producing thousand’s of giga bites of data
    • Mining such data is of primary interest but the need for privacy and security very often limits the real impact of these tasks
    • Security Issues of Outsources Databases:
    • In cloud infrastructure databases are very often outsourced based in well known Database as a service paradigm
    • .This gives raise to a security issues as query processing procedures may easily access sensitive data sets and determine privacy breach
  15. Challenges Faced by Big Data Analytics

    Slide 15 - Challenges Faced by Big Data Analytics

    • Privacy preserving Big Data Analytics:
    • Big Data is vast amount of data as well as knowledge that should be treasured as these data are useful for decision making and prediction purposes
    • Big data Exchange :
    • Data exchange methodologies will become more and more important in future due to well known characteristics of cloud computing , Here applications are likely to exchange large scale of data
    • Querying Cloud-Enabled DBMS:
    • In a analytical process data is dispersed over cloud, here to prevent privacy and security breaches a recent initiative pursues the idea then devise intelligent algorithm for querying encrypted data without preventing the accuracy of answer
    • Data Storage Issues
    • Data Accuracy
  16. Current State and future opportunities

    Slide 16 - Current State and future opportunities

    • Wealth of digital information is being generated daily and this information has a great potential values for many purposes if captured and aggregated effectively
    • Business of all shapes and sizes are tracking and storing all the customer purchases, product searches, website interactions and other information to increase the effectiveness of their marketing and customer service
    • Even Governments are keeping track of the content of blogs and tweets to perform analysis
    • public health organisations are keeping track of every new articles, tweets and web searches trends to track the progress
  17. Conclusion

    Slide 17 - Conclusion

    • Big Data is going to continue growing over the years to come, and each data scientist will have to manage a much larger amount of data every year.
    • Big Data mining will help us to discover knowledge that no one has discovered before
  18.                    Thank You

    Slide 18 - Thank You