Digital transformation is process of using digital technologies and integrating the technologies in all areas of business which transforms four important aspects including system, process, technology and people involved in an enterprise. Business organizations cannot remain without integrating digital technologies in the businesses as expectations of customers become so trendy and they want to make all business transactions via smart technologies and internet. The emerging technologies support business organization in automating their processes and facilitate improved processes. This ultimately achieves the customers’ expectations. In this paper, the need for digital transformation, steps of digital transformation and important digital transformation technologies namely cloud computing, big data, data mining, machine learning techniques, etc., are discussed.

1. https://iaeme.com/Home/issue/IJARET 419 editor@iaeme.com
International Journal of Advanced Research in Engineering and Technology (IJARET)
Volume 11, Issue 2, February 2020, pp. 419-425, Article ID: IJARET_11_02_040
Available online at https://iaeme.com/Home/issue/IJARET?Volume=11&Issue=2
ISSN Print: 0976-6480 and ISSN Online: 0976-6499
DOI: 10.34218/IJARET.11.2.2020.040
© IAEME Publication Scopus Indexed
AN INTRODUCTION TO DIGITAL
TRANSFORMATION TECHNOLOGIES
Chellammal Surianarayanan
Department of Computer Science,
Bharathidasan University Constituent Arts and Science College,
(Affiliated to Bharathidasan University), Navalurkuttapattu, Srirangam Tk.,
Tiruchirappalli-620 027, Tamil Nadu, India
ABSTRACT
Digital transformation is process of using digital technologies and integrating the
technologies in all areas of business which transforms four important aspects including
system, process, technology and people involved in an enterprise. Business
organizations cannot remain without integrating digital technologies in the businesses
as expectations of customers become so trendy and they want to make all business
transactions via smart technologies and internet. The emerging technologies support
business organization in automating their processes and facilitate improved processes.
This ultimately achieves the customers’ expectations. In this paper, the need for digital
transformation, steps of digital transformation and important digital transformation
technologies namely cloud computing, big data, data mining, machine learning
techniques, etc., are discussed.
Keywords: digitization, digitalization, digital transformation, cloud computing, big
data, blockchain, the Internet of Things
Cite this Article: Chellammal Surianarayanan, An Introduction to Digital
Transformation Technologies, International Journal of Advanced Research in
Engineering and Technology (IJARET), 11 (2), 2020, pp 419-425.
https://iaeme.com/Home/issue/IJARET?Volume=11&Issue=2
1. INTRODUCTION
The advancement of technologies has brought several changes in all walks of our life. The
emergence of the internet, network connectivity and smart phone have brought tremendous
changes in business. Digital transformation refers to the use of digital technologies in all areas
of business which ultimately changes the business processes with new avenues to meet the
customer experiences, changing business needs and dynamic market trends. Digital
transformation is basically the process of changing system, process, technology and people of
a business as in Fig. 1

2. An Introduction to Digital Transformation Technologies
https://iaeme.com/Home/issue/IJARET 420 editor@iaeme.com
Figure 1 Digital transformation
Digital transformation leads to reduced investment cost, improved financial performance,
increased employee productivity, improved customer experience and interoperability. Digital
transformation cannot happen at once but it goes through systematic steps as described in the
subsequent section.
2. STEPS OF DIGITAL TRANSFORMATION
The fundamental steps of digital transformation in an enterprise is shown in Fig. 2.
Figure 2 Steps of digital transformation
Digitization refers to the conversion of analog signals to digital signals. For example, a
physical parameter like temperature can continuously vary as a real numbered data. When it is
digitized, it can contain only discrete values and not continuous values.
Digitalization refers to the processing making business processes as automated processes.
Automated process does not require human intervention. So, by apply digitization and other
techniques & technologies, processes are automated. This aspect is referred to as digitalization.
Digital transformation basically refers to integration of digital technologies in all aspect of
a business. It actually modifies the entire business organization with (i) empowered employees
(ii) improved operations and processes (iii) automated processes (iv) improved tools and
technologies and (v) means to reach improved customer satisfaction. Digital transformation is

3. Chellammal Surianarayanan
https://iaeme.com/Home/issue/IJARET 421 editor@iaeme.com
being brought by various digital technologies. An overview of important digital transformation
technologies is highlighted in the subsequent section.
3. IMPORTANT DIGITAL TRANSFORMATION TECHNOLOGIES
3.1. Big Data
Modern smart phones offer facility to internet connection, camera, video, etc., [1] and many
data sharing applications which tend to generate huge amount of data. Similarly, social website
such as Facebook, twitter, YouTube, etc generate large amount of data. The size of data is of
the order of several Peta bytes which cannot be accommodated and normal in normal
computers. In addition, data generated by sensor network, the Internet of Things(IoT) devices,
multimedia devices etc., tend have speed associated with them (for example video streams, data
streams). In addition to volume and speed, the format of data also not a structured one. It may
contain audio, video or text based data. These data are unstructured. Thus, big data refers to a
kind of data having huge volume, variety and velocity which could not be handled by the
conventional computers and conventional database management systems. Special tools and
techniques such as Hadoop ecosystem have been developed. Here, it is clear that tools and
techniques are well equipped with big data to analyse the data associated with modern phones
and web applications. With respect to digital transformation, since customers are extensively
do their sales using smart phones and internets, enterprises can not only sell the products online
but also can analyze the marketing trends and take decision using big data tools and platforms.
Big data pave way for extracting information and knowledge from voluminous data. In addition,
big data tools and solutions can also be supported and deployed in cloud infrastructures as
described in the subsequent section.
3.2. Cloud Computing
Cloud computing is a computing paradigm where cloud service providers deliver different
computing services namely servers, storage, networks, software, etc as services over Internet to
cloud users according to their demand on a pay-as-you-go pricing model. Basically, cloud
computing paradigm has evolved to support the small and medium level enterprise to start up
their firms with infrastructure and other resources offered by cloud service providers on a rental
basis. The major benefit behind cloud computing is that companies can avoid the huge capital
cost, operational/maintenance cost and complexity involved in owning and maintaining a firm.
Nowadays not only infrastructure and software, any thing like intelligence, analytics, are
available as service. Thus, enterprises which want to implement digital transformation for their
companies can avail a wide range of services[2-3] including
(i) infrastructure(basically refers to hardware such as CPUs, servers, storage disks, networking
devices, communication devices like switch, hub, etc)
(ii) software platforms including Integrated Development Environment(IDE), run time
environment, programming languages, compilers, debuggers, linkers, loaders, etc, database
servers such as DB2, Oracle, etc
(iii) fully developed ready made software solutions such as Enterprise Resource Planning(ERP)
software, Supply Chain Management(SCM), Customer Relationship Management(CRM), etc.
Typically, enterprises, digitize their data and push the data into cloud storages for backup
and replication purposes. As far as digital transformation is concerned, at first enterprises can
very well migrate to cloud for automation of their processes and can host the processes with
cloud infrastructure. Here, the host applications are well maintained for their different versions.
Software updates, license of software, etc., are taken care of by cloud service providers. Here,

4. An Introduction to Digital Transformation Technologies
https://iaeme.com/Home/issue/IJARET 422 editor@iaeme.com
one can understand that the cloud users are totally relieved from infrastructure related issues
and they can fully focus only on their actual development/domain related issues.
Secondly, enterprises can store all the data in cloud data storage for backup or replication.
Any enterprise wants to safeguard its data as the data is like to be lost during natural disasters
such as Tsunami or any other system level malfunctioning or system crash. Beyond all, the
unique feature of cloud is it can accommodate all the dynamically varying resource
requirements and offer the required resources on demand to users in an elastic manner in couple
of minutes.
3.3. Data Mining and Machine Learning Techniques
Having described about above the generation of huge data from various sources, the enterprises
should be able to discover knowledge from data. Data mining tasks such as data aggregation,
data summarization, data characterisation, dimension reduction, finding associations or
relationships among data are being employed to extract useful information. In addition, machine
learning algorithms are used to train machines to learn the given input data and train them to
take decisions based on the learnt knowledge. Once trained, the machines can mimic human
and become able to take intelligent decisions.
Broadly speaking machine learning algorithms are of two types, supervised and
unsupervised [4-5]. Unsupervised algorithms learn from data on its own and partitions the data
according to the similarity among the data items. For example, clustering algorithms are
unsupervised. Supervised algorithms learn from given data with the help of guiding inputs that
are given during training. For example, classification algorithms are supervised algorithms.
Classification labels are given and guiding input to algorithms. So, the machines look into the
data and generate rules that classify the data into the predefine class labels. In addition,
classification algorithms find many applications in healthcare domain, disease prediction in
plants, fraudulent detection in financial domain, intruder detection in telecommunication and
networks etc. Nowadays deep learning techniques, another category of deep learning using
neural networks are very much useful in image processing based applications.
3.4. Blockchain
Blockchain is a technology in which many transactions called blocks are grouped and
distributed among the users and the unique feature blockchain technology is that the data is
immutable and hence it does not need any other techniques or solution to prove the integrity of
the data. Blockchain is a decentralized network to provide data security and transparency
without requiring any central authority to validate the transactions.
Figure 3 Core elements of blockchain

5. Chellammal Surianarayanan
https://iaeme.com/Home/issue/IJARET 423 editor@iaeme.com
This is achieved through what is called consensus protocol. Core elements of blockchain
technology consist of (i) hash algorithm, (ii) immutable ledger (iii) peer to peer network and
(iv) consensus protocol as shown in Fig. 3.
Hash Algorithm
Hash algorithm is a cryptographic function which converts any input to a fixed size output
string. Whatever it may be the length of an input data, the output length is fixed. In addition,
for each unique input, it produces the same output string. More importantly hash functions are
one way functions. In blockchain, each block is a group of transactions. Each block contains its
hash of the block. In addition, the hash of a block is transmitted to its successor block. It means
that each block contains its hash as well as the hash of previous block. Since each block has the
hash of previous block, if any hacker attacks the any block, its hash will change and it will be
communicated to next block and so on, through the entire blockchain
Immutable ledger
Consider 3 nodes, node-1, node-2 and node-3 in a blockchain as in Fig. 4. As in Fig. 4, each
and every node contains the immutable ledger[6]. Once a transaction is added into the ledger,
it cannot be altered. It becomes an immutable record. So, as mentioned above, if any hacker
alters any of the block, its hash changes and changes will be successively communicated. Such
changes will be discarded and the integrity of the data will be maintained. The important aspect
behind the blockchain is that, it is an append only register.
Figure 4 Availability of ledger in all the blocks of the chain
Peer-to-Peer Network
When a transaction is created, the concerned node broadcasts the transaction to all the peer
nodes in the network.
This new transaction will be validated by the consensus protocol

6. An Introduction to Digital Transformation Technologies
https://iaeme.com/Home/issue/IJARET 424 editor@iaeme.com
Consensus Protocol
The newly created transaction will be submitted for verification to all the peers available in the
blockchain. Consensus protocol is a set of rules based on which the nodes will verify whether
the newly created transaction is valid or not. Since, blockchain technology does not have a
centralized authority for validation of the new transaction, every peer should arrive at a common
consensus protocol. There are various consensus protocols namely Proof of Work(PoW) and
Proof of Stack(PoS)
3.5. The Internet of Things(IoT)
The Internet of Things (IoT) is the network of physical objects or "things" embedded with
electronics, software, sensors, and network connectivity, which enables these objects to collect
and exchange data [7]. Basically, the IoT can connect several devices which can share their data
with evolving interoperable communication technologies[8]. In IoT life cycle, 4 steps are
involved. Different sensors collect data, communicate the data to a server and the data is
analysed. According to analysis, suitable actions are taken. These steps are shown in Fig. 5.
Figure 5 Steps of the IoT life cycle
One of the unique features of the IoT is that very frequently it uses cheap sensors, but a lot
of information is acquired and conveyed to the central controller in real time. So, actions can
be taken in real time without any time latency. This technology finds lot of applications in
healthcare. For example, a remote health monitoring system. In this system, various IoT sensos
which monitor the vital parameters of a patient, say, heartbeat, pressure, blood glucose, etc and
communicate to central station. After monitoring the acquired data, a physical can go for
decisions like whether the patient needs any immediate attention or not.
4. CONCLUSION
In this paper, the need for digital transformation for modern business is presented. Digital
transformation becomes mandatory for almost any organization as the modern technologies
influence the way of everyone’s life. In order to meet the dynamic changes in business
requirements and marketing trends, organizations have already started equipping their business
trends integrated with various evolving technologies such as big data, cloud computing, the IoT
etc. After discussing the significance of digital transformation, how the transformation is being
taking place through digitization, digitalization and transformation over entire business are
presented. An overview of important digital technologies is presented.
REFERENCES
[1] Muhammad Anshari, Yabit Alas, “Smartphones habits, necessities, and big data challenges”,
Journal of High Technology Management Research, Volume 26, Issue 2, 2015, Pages 177-185
[2] D. Puthal, B. P. S. Sahoo, S. Mishra and S. Swain, "Cloud Computing Features, Issues, and
Challenges: A Big Picture," 2015 International Conference on Computational Intelligence and
Networks, 2015, pp. 116-123, doi: 10.1109/CINE.2015.31

7. Chellammal Surianarayanan
https://iaeme.com/Home/issue/IJARET 425 editor@iaeme.com
[3] Aishwarya Srinivasan, Abdul Quadir, V. Vijayakumar, “Era of Cloud Computing: A New
Insight to Hybrid Cloud”, Procedia Computer Science, Volume 50, 2015, Pages 42-51,
https://doi.org/10.1016/j.procs.2015.04.059
[4] Ayon Dey, “Machine learning algorithms: A review”, International journal of Computer
Science and Information Technologies, vol. 7(3), 2016, 1174-1179
[5] Susmita Ray, “ A quick review of machine learning algorithms”, International Conference on
machine learning, big data, cloud and parallel computing, 14-16th
Feb 2019, pp.35-39, IEEE,
2019
[6] Atlam, Hany F., Alenezi, Ahmed, Alassafi, Madini O. and Wills, Gary (2018) Blockchain with
Internet of Things: benefits, challenges, and future directions. International Journal of
Intelligent Systems and Applications, 10 (6), 40-48, (doi:10.5815/ijisa.2018.06.05)
[7] Keyur K Patel, Sunil M Patel, “Internet of Things-IOT: Definition, Characteristics,
Architecture, Enabling Technologies, Application & Future Challenges”, International Journal
of Engineering Science and Computing, vol. 6, issue 5, May 2016, pp. 6122-6131
[8] ITU, “Overview of the Internet of things,” Ser. Y Glob. Inf. infrastructure, internet Protoc. Asp.
next-generation networks - Fram. Funct. Archit. Model., p. 22, 2012.