This document discusses the opportunities and challenges of big data. It defines big data as huge volumes of structured and unstructured data from various sources that require new tools to analyze and extract business insights. Big data provides both statistical and predictive views to help businesses make smarter decisions. While big data allows companies to integrate diverse data sources and gain real-time insights, challenges include processing large and complex data volumes and ensuring data quality, privacy and management. The document outlines the big data lifecycle and how analytics can be used descriptively, predictively and prescriptively.

1. Big Data
Challenges and Opportunities

2. Opportunities and Challenges
• Effective use of data in competition.
• Business needs data from information to make better, smarter
decisions ahead of competitors.
• Big Data is supplementing the data, including structured,
unstructured data, machine and online/mobile data.
• Big Data will change the fundamental way business compete
and operate.
• Big Data provides both statistical and predictive views.
• Even though ability to capture huge amount of data has
grown, the technical capacity to analyze data just started.
• Business requires faster tools to analyze data and provide
business with real time data.

3. What is Big Data
• Big Data refers to huge volumes of data, created by
people/tools/machines. This requires new tools to analyze, in order to
provide business insights that relate to customers, risk, performance and
productivity.
• Big Data is the collection of data which is gathered from internet, phones,
video and voice recordings and data can be either structured or
unstructured.
• Big Data has four properties and typically characterized by FOUR “V”s.
• Volume : The amount of data is so vast when compared to traditional
data.
• Variety : Data comes from different sources, both from machines/people.
• Velocity : Data generated very fast from different sources like 24 X 7.
• Veracity : Data collected from different places and we need to check
quality of data captured.

4. Life Cycle
• Creation : Along with traditional data, new data has been created
from social network/videos/voice, which are never used before and
helped business to understand customers more to launch their
products.
• Processing: Even though organizations has huge data, they were
unwilling to process data, as it was out weighting the benefit of
data being processed. But with the help of new technologies like
Hadoop and with distributed storage, the cost of processing data
came down drastically.
• Output: The data should be available readily to the right people to
make insightful decisions leading to successful outcomes.
Organizations putting more importance to employees(Data
Scientist) who are specialized in analysis of data.

5. Big Data and Analytics
• The goal of Analytics is to improve the efficiency and
effectiveness of every decision or action.
• Analytics is the discovery of communication of meaningful
patterns of business data.
• Analytics enables organizations to meet stakeholder reporting
needs of market, risk etc., and helping organization to
perform better.
• Organization should have right combination of people,
process and technology.

6. Analytics
• Descriptive Analytics: This is Business
Intelligence and deals with what has happened
already like last month sales.
• Predictive Analytics: To predict what is going to
happen in different sceneries depending of past
data.
• Prescriptive Analytics: To determine which
decision/action will produce the most effective
result against a specific set of objectives and
constraints.

7. Big Data Benefits
• Big Data helps to get data from new external sources in a cost
effective manner.
• As per estimation 85% of data is unstructured and Big Data helps in
getting this data processed in lower prices.
• Big Data allows organizations to collect data from various sources.
• It allows the data to be stored at lowest level and for prolonged
period. Possible to integrate massive volumes of data in various
formats.
• Customers can be provided with consolidated reports views which
helps in intelligent business decisions. And monitoring customer
profiles
• Healthcare industry adopted Big Data and resulted in helping
researches further.
• Helps in Helps in company offering services which customers
preferred.

8. Big Data Benefits -- Continued
• Possible to integrate massive volumes of data in various
formats.
• Customers can be provided with consolidated reports views
which helps in intelligent business decisions.
• Helps in monitoring customer profiles
• Helps in company offering services which customers
preferred.
• There is no special storage required and Big Data can be
deployed on commodity hardware.
• With the help of low cost computing number of big data
forecasting ventures have risen which are predicting exact
whether.

9. Big Data Risks
• Modeling, storage and processing challenges arise from the
growing of data volumes.
• Challenge in unifying different data sources.
• Too much of data to be processed which results in noise.
• No ready made tools to process data.
• Not enough skilled employees not available process build big
data solutions.
• Integrated data archicture increases the challenge of data
linkages and matching lagorithms.
• Incerase in complexity of data.

10. Big Data Risks -- Continued
• It should have consistent guidance, procedure
and clear management decisions.
• Data should be shared at right level in the
organization.
• Managers need to embrace new technology.
• Has to consider ownership and privacy of data.
• It may bring intellectual property issues and its
big challenges that employees are not sharing the
data outside of organization.

11. Summary
• Big Data become a success factor for companies by providing
relevant information at right time.
• Big Data helped financial sector(Credit Cards/Banks) with
fraud detection, which prevented revenue loss.
• With Big Data it become possible to integrate different types
of data and get the real time data at right time.
• Increasingly started used in Health Industry and this is helping
especially in Pharmacy and Disease detection.
• Companies started using Big Data in selection process of
employees.