Unit 10: Big Data and Business Analytics
Assignment 1
Introduction
In this assignment I am going to research and investigate, how the companies use Big Data,
how do they do Data Analytics and how do they use this to improve their services. So, this is
included in researching on different methods, strategic planning, processing lots of data
and the challenges the company will face using Big Data.
How do Companies Improve Performance by Using Data Analytics?
Now days, businesses facing lots of competition with other companies. To stay ahead, of
many companies’ businesses use data analytics to improve their productivity and make
better decisions for their business to find new ways to grow in the market. By collecting and
learning large amounts of data, they can find new ways to plan their market strategy.
Why Data Analysis is Important?
Understanding Customers: By doing data analysis businesses learn about their customers.
To see who their customers are, what do they buy, when do they shop and how often do,
they do it. This helps companies to predict their trends, create better products, and design
their products in a way that have demand on their audience.
Improving How the Business Runs: Business by studying their operations, they can find the
areas they need to improve on, such as in supply chains, sales, or marketing. For example,
they can find the problems like having delays or removing the waste and by fixing this
problem it will save the company time and money.
Creating New Products and Services: Data helps businesses to improve their product and
help them to come up with new ideas. To do this they can look at customer feedback and
market trends to stay to stay ahead of competitors and grow their sales.
Tools for Data Analysis
,To analyse data, companies use different types of tools to help them to collect, store and
study the data. Each tools have its own advantages to handle specific data.
Hadoop: Hadoop is a big storage for data. It helps the companies to keep and manage lots
of data. This tool also is good for processing big data, because it split the big data into
smaller pieces of data so it can be handled at the same time.
MongoDB: MongoDB is a database, but it’s different from other traditional ones. It works
well when the data is not in the format, it supposed to. For example, if the data keeps
changing or has different shapes, MongoDB can still handle it without problems. It will be
like in JSON format.
Talend: This tool help data to be collected from many different places and it’s put all the
data together. It ensures that data is clean, organised, and ready for analysis. And this
makes it easier for companies to understand and use the information correctly.
Apache Cassandra: Cassandra is a database which is designed to work across multiple
computers or servers. It is best for to store large amount of data, and it is reliable, which
means that it won’t lose data even if one server has issues.
Apache Spark: Spark also is a helpful tool because it can process the data quickly. If a
company needs to handle complex tasks or needs to analyse huge amounts of data in a
short time, Spark can do this efficiently by working with the data in the memory instead of
using slower storage systems.
How Data Analytics Helps Big Companies?
Big Companies like Amazon, Google, and Facebook use data analytics to understand about
their customers, predict the needs, and stay innovative in the market. By using these data
analytics tools, they can process the data quickly and it will help them to come up with new
ideas which will help them to succeed.
Why Data Analytics Matters?
Using data analytics is now important for businesses because it helps them make best
decision, solve problems, and adapt to change they need to do it in the business. The
companies that are interested in this approach can stay competitive and they can succeed in
the long run in the market.
, General Challenges of Analysing Data, Skills Required & Security Issues
When companies start collecting data for a specific reason, they often face challenges while
they are collecting the data. These challenges are include making sure the data is good
quality, to see if they data will help the company or not when they and keeping the data
being stolen.
Data Quality
Taking the good quality of is very important for a company to be get success. The data needs
to be reliable, accurate, and detailed to help the company to make best decisions and plans
for the future. If the data quality is not that good like it comes from bad sources, was
collected in the wrong way, or wasn’t cleaned properly it could lead to have mistaken when
the company will try to analysis the data. And this can have impact on the company, such as
losing customers, damaging their reputation and losing trust from other business. For
modern companies it is important to have good quality of data for analysis.
Data Security
To keep the data safe is one of the big challenges for companies. Because while collecting
and analysing data, they handle sensitive information like people’s personal details, what
they buy, and their habits. Because these are the important data of the customer, so the
company needs to make sure, they store in a secure place.
At every step of handling data, the companies must protect the data. If there is a security
breach, the sensitive data could be exposed, leading them to have serious problems like
legal trouble, losing the customer trust, and having financial losses.
Data Integration
Sometimes, the companies collect data from different places, so to manage the data it can
be hard for them because they need to put all the data together. Without having the right
tools for the data, this process can be complicated, and it might take lots of time for them.
To solve this problem, companies need to build a system which will help them to bring all
the data together. They can use the central storage system which is called "data warehouse"
Assignment 1
Introduction
In this assignment I am going to research and investigate, how the companies use Big Data,
how do they do Data Analytics and how do they use this to improve their services. So, this is
included in researching on different methods, strategic planning, processing lots of data
and the challenges the company will face using Big Data.
How do Companies Improve Performance by Using Data Analytics?
Now days, businesses facing lots of competition with other companies. To stay ahead, of
many companies’ businesses use data analytics to improve their productivity and make
better decisions for their business to find new ways to grow in the market. By collecting and
learning large amounts of data, they can find new ways to plan their market strategy.
Why Data Analysis is Important?
Understanding Customers: By doing data analysis businesses learn about their customers.
To see who their customers are, what do they buy, when do they shop and how often do,
they do it. This helps companies to predict their trends, create better products, and design
their products in a way that have demand on their audience.
Improving How the Business Runs: Business by studying their operations, they can find the
areas they need to improve on, such as in supply chains, sales, or marketing. For example,
they can find the problems like having delays or removing the waste and by fixing this
problem it will save the company time and money.
Creating New Products and Services: Data helps businesses to improve their product and
help them to come up with new ideas. To do this they can look at customer feedback and
market trends to stay to stay ahead of competitors and grow their sales.
Tools for Data Analysis
,To analyse data, companies use different types of tools to help them to collect, store and
study the data. Each tools have its own advantages to handle specific data.
Hadoop: Hadoop is a big storage for data. It helps the companies to keep and manage lots
of data. This tool also is good for processing big data, because it split the big data into
smaller pieces of data so it can be handled at the same time.
MongoDB: MongoDB is a database, but it’s different from other traditional ones. It works
well when the data is not in the format, it supposed to. For example, if the data keeps
changing or has different shapes, MongoDB can still handle it without problems. It will be
like in JSON format.
Talend: This tool help data to be collected from many different places and it’s put all the
data together. It ensures that data is clean, organised, and ready for analysis. And this
makes it easier for companies to understand and use the information correctly.
Apache Cassandra: Cassandra is a database which is designed to work across multiple
computers or servers. It is best for to store large amount of data, and it is reliable, which
means that it won’t lose data even if one server has issues.
Apache Spark: Spark also is a helpful tool because it can process the data quickly. If a
company needs to handle complex tasks or needs to analyse huge amounts of data in a
short time, Spark can do this efficiently by working with the data in the memory instead of
using slower storage systems.
How Data Analytics Helps Big Companies?
Big Companies like Amazon, Google, and Facebook use data analytics to understand about
their customers, predict the needs, and stay innovative in the market. By using these data
analytics tools, they can process the data quickly and it will help them to come up with new
ideas which will help them to succeed.
Why Data Analytics Matters?
Using data analytics is now important for businesses because it helps them make best
decision, solve problems, and adapt to change they need to do it in the business. The
companies that are interested in this approach can stay competitive and they can succeed in
the long run in the market.
, General Challenges of Analysing Data, Skills Required & Security Issues
When companies start collecting data for a specific reason, they often face challenges while
they are collecting the data. These challenges are include making sure the data is good
quality, to see if they data will help the company or not when they and keeping the data
being stolen.
Data Quality
Taking the good quality of is very important for a company to be get success. The data needs
to be reliable, accurate, and detailed to help the company to make best decisions and plans
for the future. If the data quality is not that good like it comes from bad sources, was
collected in the wrong way, or wasn’t cleaned properly it could lead to have mistaken when
the company will try to analysis the data. And this can have impact on the company, such as
losing customers, damaging their reputation and losing trust from other business. For
modern companies it is important to have good quality of data for analysis.
Data Security
To keep the data safe is one of the big challenges for companies. Because while collecting
and analysing data, they handle sensitive information like people’s personal details, what
they buy, and their habits. Because these are the important data of the customer, so the
company needs to make sure, they store in a secure place.
At every step of handling data, the companies must protect the data. If there is a security
breach, the sensitive data could be exposed, leading them to have serious problems like
legal trouble, losing the customer trust, and having financial losses.
Data Integration
Sometimes, the companies collect data from different places, so to manage the data it can
be hard for them because they need to put all the data together. Without having the right
tools for the data, this process can be complicated, and it might take lots of time for them.
To solve this problem, companies need to build a system which will help them to bring all
the data together. They can use the central storage system which is called "data warehouse"
