Digital Information Management and Big Data Analytics Report

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DIGITAL INFORMATION MANAGEMENT

Contents
Abstract.................................................................................................................................................2
Introduction...........................................................................................................................................2
Theoretical perspective.........................................................................................................................2
Digital information management......................................................................................................2
Understanding the concept of Big Data.............................................................................................3
Generating Insights and value from enterprise data through big data..............................................3
Type of Big Data:................................................................................................................................4
Characteristics of Big Data.................................................................................................................6
Findings.................................................................................................................................................7
Reflection..............................................................................................................................................7
Conclusion and Recommendation.........................................................................................................8
References.............................................................................................................................................9

Abstract
The digital information management is very important and organizations must understand
methods through which they can get value and information from available data. The main
aim of the report is to understand digital information management concepts and practices
with respect to Big Data technology. A detailed and thorough study of Big Data concepts and
its effectiveness with the organization making process was analysed. The report successfully
details all major Big Data concepts.
Introduction
Organizations that have adopted digital information management approach and utilize
analytical tools for decision making are able to outperform their competition. From the last 5
years, there is a significant rise in the number of the organization using Big Data technology
for cost-effective management of data. Organizations are using data and analysis for fact-
based decision making (Chaffey and White, 2011).
According to the CEB large number of organizations will expand their information
management efforts in order to make sure that general employee gets access to data. The
organizations have to improve the core information delivery system, to store a large amount
of data they need to use unstructured data (Bhadani and Jothimani, 2016).
Theoretical perspective
Digital information management
Information management is defined as the process of managing, maintaining, storing,
collecting and processing of data and information. Nowadays data and information have
become the most important asset for the organizations. Companies with access to information
will have a competitive advantage over other businesses. Information management involves
the use of policies and procedure for managing and sharing of information among individuals
(Akerkar, 2013).
Information management is a way, through which organizations manage, distribute, store and
process digital information. The organization can achieve Information management through
the use of information management systems. Just having access to information is not

beneficial for organizations, they must analyse data and try to extract valuable insights from
available data.
Organizations that have adopted digital information management approach and utilize
analytical tools for decision making are able to outperform their competition. From the last 5
years, there is a significant rise in the number of the organization using Big Data technology
for cost-effective management of data. Organizations are using data and analysis for fact-
based decision making (Chaffey and White, 2011).
According to the CEB large number of organizations will expand their information
management efforts in order to make sure that general employee gets access to data. The
organizations have to improve the core information delivery system, to store a large amount
of data they need to use unstructured data (Bhadani and Jothimani, 2016).
Understanding the concept of Big Data
Before understanding about Big Data it is important to understand data. Data is referred to the
quantity, a character or symbol on which the computer system can perform operations. The
digital data can be transferred through the electrical signals and stored on the optical device.
BigData is also data but big Data grows with time. The Big Data term is used to describe a
large amount of data that is growing exponentially with time. In other terms, BigData is a
collection of data that is huge in size. The BigData is very large and complex that the
traditional data management tools are unable to manage the data (Akter and Wamba, 2016).

Generating Insights and value from enterprise data through big data
Statistics show that around 500 terabytes of data are generated by Facebook daily. The main
source of the Facebook data is the photo and video upload, messages and comment text etc.
The advancement in the data storage technology and large customer base have resulted in
large scale data generation. Global brands like Facebook use their own data centres for
storing a large amount of data. Companies like Microsoft, Facebook and Amazon have
developed their own data centres.
A single jet engine can generate around 10 terabytes of data in 30 minutes of operation. There
are a lot of flights operating daily. This can easily generate data in petabytes. The aviation
industry can use this data for getting important insights about the flight operation. The data
can be very beneficial for the airline industry.
The above two example of Facebook and an airline company are generating a lot of data. The
company can use a data analysis tool such as the Big Data analysis and get important
information. Facebook use this strategy, they collect data from customers and use that data to
run their online advertisement business (Kache and Seuring, 2017). Through data analysis,
the company is able to analyse the customer’s data. The company data is one of the main
assets of the company. Data has helped the company in becoming a multi-billion global
organization.
The huge amount of data generated by the aviation business can be very beneficial. Aviation
company can use data analysis and understand the real-time performance of flight operation.
Aviation companies are using this data for analysing the most cost-effective route. This helps
the company in saving operation cost as well the time. Data is helpful in understanding the
customer’s behaviour. The companies can use customer data to analyse their need and
demand and offer products that can attract new customers. Therefore from the above
discussion, it is clear that management of Big Data can be challenging but its proper analysis
and utilization can bring new opportunities for the business (Laudon and Laudon, 2016).
Type of Big Data:
1) Structured
2) Unstructured
Structured data:

Any data that can be stored, managed and processed and is present infix form is referred to as
structured data. The advancement in computing technology and data management techniques
has resulted in the development of data management systems. The structured data is easier to
store. A relational database is used for storing structured data. The data scientists have
developed systems that can be used for finding value from the data. But nowadays the size of
data is growing at very rapid speed. Traditional relational databases are not designed for
managing large data (McAfee, 2012).
A relational database store data in the form of tables. The structure data have a specific
format, therefore, monitoring, management and processing of structured is simple. Employee
data stored in a relational database is an example of a structured form of data.
Unstructured Data:
Data available in unknown form or structure is known as the unstructured data. The unknown
form and structure pose a great challenge. The unstructured data can be huge making it very
difficult for monitoring, management and processing of data. NoSQL database such as the
MongoDB is used for management and storage of structured data. Video, audio, image and
simple text are examples of unstructured data. Nowadays most of the data that is generated is
unstructured data. Organizations have a lot of data but they don't know how they can analyse
the data and generate valuable insights from unstructured data.

Characteristics of Big Data
Volume: The Big Data itself is related to the enormous size of data. The size of the data is
very important as it helps in finding crucial information and value from the data. Also, it is
the volume of the data that define if particular data can be considered as the Big Data or not.
Hence the volume of data should be considered while dealing with big data (Kwon et al.,
2014).
Variety: Variety is referred to the different forms of data, Big Data deals with both structured
and unstructured data. Earlier the database and spreadsheets were only considered as data.
Big Data deals with both structured and unstructured data. Unstructured data includes audio,
video, email and images. The variety of data poses challenges in storage, management, and
processing of data.
Velocity: is referred to the speed through which the data is generated. The generation of data
with such speed creates challenges in management, storage and processing of data. A
datacentre is used for storage of a large amount of data. The real-time data analysis can
provide key insights and information. Advancement in BigData technology brings a lot of
opportunity for organizations (Fichman et al., 2014).
Variability: It is referred to as the inconsistency of data. The variability of data can cause
hindrance in data management.

Findings
A large number of employees depends on data for business decision making. Therefore the
managers must ensure that correct data is available. All major decisions nowadays are taken
with the help of data. Therefore it is very important that the managers are able to provide
access to correct data at the right time. The importance of data increases if the data is not only
available but the employees have trust in the organizational data (Peppard and Ward, 2016).
Data can be present in any form, it is the duty of managers to ensure that the employee gets
correct data. Companies can use data analysis tools for the proper analysis of data. A large
number of employee thinks that corporate data is usable. Use of proper mechanism and
information management will help the organizations in making surer that the available data is
useful to the business (Chaffey and White, 2011).
Less than 40% of the organizations have any proper mechanism and expertise to drive value
from big data. For Big Data analysis the expert skill and knowledge are required. It is
recommended that every organization maintain an expert Big Data team. Businesses can
utilize data analysis for making business decisions Nowadays businesses use sophisticated
tools for taking out value from the data. The decision-making process is one of the most
responsible and important tasks of managers (Sukumar and Ferrell, 2013). The availability of
the right data at the right time will make sure that the company's top management is able to
take effective business decisions. The Big Data analysis will provide key insights and data.
The organizations that will have access to data will have a better opportunity. They can use
big data technology combined with other tools such as BI, visualization, analytics. Use of big
data technology in customer’s service will help the company in finding the current and future
demand of customers (Rubinstein, 2012).
1. Identification of risk to products and services
2. Big data can help in improving the business operation of the company
Reflection
With an increase in technological capability, the organization must understand how these
technologies relate to the wider business operations and digital information management and
must make sure that they are capable of using Big Data technology. Since many years of data,
driven companies are struggling with the effective use of data. Most of the data generated by
these companies are mostly unstructured data. It cannot be stored in a relational database
(Sousa and Oz, 2014). Big data is just a technology, but when used effectively it can drive

important solutions and business value for organizations. The organization can combine Big
Data technology with relational database technology and other technologies such as Business
Intelligence, Spatial, visualization and many more, offers potential to unlock information that
was earlier difficult to analyse and manage (Verhoef et al., 2016). Big Data brings a range of
new processes and designs that can help in the effective management of information. It can
make digital information management less brittle, speedy delivery of data and improve the
overall business. From the above discussion, it can be concluded that organizations can use
Big Data technology for effective management of digital information. More than 80% of the
employee in a big organization believes that they need access to data for making important
decisions (Akter, 2016). The organizations are responsible for making data available to their
employees. Organizations must ensure that the organizational data is accessible at any time
and nay where. The advancement in information and communication technology has a great
impact on the organizations and their data (Wanget et al., 2018). Now users can use their
smartphones to access data at any time. Now the data is regarded as the new oil.
Organizations should understand the importance of data and information. Access to correct
information at the right time is very important. Large numbers of organizations are adopting
the BOYD (Bring Your Own Device) concept. Large numbers of employee prefer to bring
their personal device to the workplace. Generally, employee use their own device to access
data, they will like to access corporate data through their personal device this will create a
great challenge to the organization as the IT department will have to integrate systems in
order to provide data and information to employees (Akerkar, 2013).
Conclusion and Recommendation
Nowadays business data is growing at rapid speed. The management of a large amount of
data is creating a lot of challenges to the organization. Access to a large amount of data
especially the big data creates more challenges then they solve any problem. A large amount
of data is creating data noise for the employees. It creates a hurdle for data analysis and leads
to ineffective decision making. The IT managers will have a greater role to make changes
within the system (Cox, 2014). The managers will have to make necessary changes and create
innovative and efficient information management systems. According to the research, the
company leaders should access the top challenges to data and try to devise their strategy
accordingly. The IT experts will be responsible for understanding the data usability and

enable data-driven decision making. They must know the impact of Bigdata and the future of
the corporate IT departments (Fichman, 2014).
References
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