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Fundamentals of Big Data and Data
Analytics
Q1. On the path
towards industrial and social progress Tata Power-DDL has always been a front
runner in introducing reformative solutions such as Smart Grid Operations,
Automatic
Meter Reading,
etc. to the power segment in North & North-West Delhi. Among other
challenges, revenue leakage and power theft were causing a roadblock in Tata
Power-DDL's goal to optimize the power supply for consumers at reduced tariffs.
By digitalizing
the power distribution systems, Tata Power - DDL opened the doorway to a vast
amount of information that was heterogenous and unstructured. With an aim to
enhance decision-making and optimize entire utility ecosystem, Tata Power-DDL’s
outlook was to employ advanced digital technology like Big Data analytics.
Tata Power-DDL
partnered with Hitachi Systems Micro Clinic to leverage their IT X OT expertise
for social enhancement. Collaborating with Tata Power-DDL, Hitachi designed a
holistic blueprint for the implementation of end-to-end advanced data analysis
solutions; deploying world-class technologies to streamline data ingestion from
diverse platforms, systematize scheduling of data and execute data engineering
on big data along with swift advanced analytics.
By creating an
advanced and reliable system architecture for big data analytics using IT X OT,
Hitachi provided Tata Power-DDL with an operational advantage by focusing on:
• IT integration objectives
• Solution modifications
• Speedy execution by using efficient
operation technology and result optimization
• Power Operation Technology
Thus, improving operational efficiency and accelerating the delivery of
true value to the society by curbing power losses and reducing tariffs for
consumers.
a. In this case, how Big data
analytics will enable prevention of revenue leakage in power sector. Which
tools can be leveraged for data ingestion, scheduling as well as final operationalization of analytics?
b. How is distributed computing
different from parallel computing? Use this context to explain the difference.
c. Which analytics methodologies
can be used to analyse the business problems mentioned in the case? Which
business metrics will be useful to track the possible fallacy in meter reading?
(10 Marks)
Ans 1.
Introduction
Tata Power Delhi Distribution
confined is a joint merger between the government of Delhi and North Delhi
strength. In July, it started to operate in 2002 to serve 7 million in north
and northwest Delhi. The company operates in 510 sq. km. Location with a peak
load of approx 2074 MW. It is the first to
Q2. State
3 use-cases of business analytics within the banking industry, highlighting
usage of descriptive, predictive, and prescriptive analytics. Give an example
of how mobile analytics is relevant for the industry and the resultant impact
vs. the traditional banking systems. (10 Marks)
Answer 2.
Introduction
The descriptive analysis includes
processing and figuring out diverse patterns and summarizing data obtained thru
reporting. Consumer segmentation is based totally on their spending nature.
Likewise, customer offers and discounts are based on segmentation. Information
analytics is the backbone for the banking industries and credit score businesses.
Statistics analytics has furnished a broader scope for the growth and
improvement of banks. It is a full-size component to analyze via search,
conduct, and forecasts to assist the banking industries. For economic
institutes,
3.a.
Explain how prescriptive analytics has increasingly been adopted along with big
data in the companies. You can also mention the relevant stakeholders in the
business who are needed to make this a success. (5 Marks)
3.b.
Mention 2 business examples of prescriptive analytics which are fueled by the
Big data and Mobile Analytics revolution with the necessary context and
methodology. (5 Marks)
Ans 3(A).
Introduction
Prescriptive evaluation is helpful to
understand which expansions are helpful and whether or not it's far worthwhile.
It is a discipline thru which corporations could make high-quality selections
in the given situation. This analytics is essential because it offers lengthy
period economic
Answer
3(b).
Introduction
A manufacturing industry could draw
extra company information. It refers to the ones businesses mounted ultimately.
It's miles helpful to do away with vital information to supply the favoured
outcomes. It specializes in the proper allocation of resources and increases
efficiency to function.
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