Big data refers to large amounts of structured and unstructured data that organizations collect and must manage. It requires new techniques and tools to analyze in order to gain useful insights. Big data comes from all digital and paper records companies store, including data in clouds and bookmarks. While not all data is digitized or structured, it is still considered big data. Big data can be analyzed to produce different results and predictions. Key factors enabling big data are increased storage, processing power, and the vast amount of data created every day. Examples of big data use include Walmart's customer transactions, Facebook photos, and decoding the human genome. Benefits are making better decisions, targeting customers, and exploring new opportunities worth over $100 billion annually.

1. CASE STUDY#4: BIG DATA Mehreen Shafique
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What is Big Data? Big Data’ is similar to ‘small data’, but bigger. But having data bigger it requires different
approaches, Techniques, tools and architecture.With an aim to solve new problems or old problems in a better
way.
 The data lying in the servers of companies was just data until yesterday – sorted and filed
 The term covers each and every piece of data an organization has stored till now
 It includes data stored in clouds and even the URLs that you bookmarked
A Company might not have digitized all the data and might not have structured all the data already but then,
all the digital, papers, structured and non-structured data with your company is now Big Data. In short, all the
data – whether or not categorized – present in your servers is collectively called BIG DATA.
How can it be used?
 To get different results using different types of analysis
 It is not necessary that that all analysis use all the data
 Different analysis uses different parts of the BIG DATA to produce the results and predictions necessary
 Big Data is essentially the data that you analyze for results that you can use for predictions and for
other uses
Why Big Data?
Key enablers of appearance and growth of Big Data are
 Increase of storage capacities
 Increase of processing power
 Availability of data
 Every day we create 2.5 quintillion bytes of data
 90% of the data in the world today has been created in the last two years alone
Examples of Big Data:
The first organizations to embrace it were online and startup firms. Firms like
 Google, eBay, LinkedIn, and Facebook were built around big data from the beginning
 Like many new information technologies, big data can bring about dramatic cost reductions
 Substantial improvements in the time required to perform a computing task, or new product and
service offerings
 Walmart handles more than 1 million customer transactions everyhour
 Facebook handles 40 billion photos from its user base
 Decoding the human genome originally took 10years to process; now it can be achieved in one week
Benefits of Big Data
 Real-time big data isn’t just a process for storing petabytes or exa bytes of data in a data warehouse,
it’s about the ability to make better decisions and take meaningful actions at the right time
 Newest research finds that organizations are using big data to target customer-centric outcomes, tap
into internal data and build a better information ecosystem
 Big Data is already an important part of the $64 billion database and data analytics market
 It offers commercial opportunities of a comparable scale to enterprise software in the late 1980s
 And the Internet boom of the 1990s, and the social media explosion of today
Future of Big Data
 $15 billion on software firms only specializing in data management and analytics
 This industry on its own is worth more than $100 billion and growing at almost 10% a year which is
roughly twice as fast as the software business as a whole
 The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44x
between 2009 and 2020