AI and Machine learning are impacting digital transformation and it is becoming crucial for every business to bend its way of doing business towards Data science for it to survive. As the field of Data science grows, every day, some factors are shaping all these changes we are seen and yet to see. Read more: https://mayurrele.net/factors-shaping-the-field-of-data-science/

1. FACTORS SHAPING
THE FIELD OF DATA
SCIENCE
Mayur Rele

2. Data science is changing as technology
advancement is continuing to shape our
future. Modern business is evolving and
getting transformed by big data and AI to
make business decisions that are causing
great impact due to the application of Data
Science in analyzing and predicting the
future. For any organization to gain a
competitive advantage, even survive in this
ever-changing environment, it must use
advanced technology for it to thrive,
therefore, many companies are being forced
to overcome these challenges by the use of
Data science to stand out.

3. This is inevitable, organizations must adapt
to the new reality and change the way they
do business and business models because
business is not as usual anymore. Things are
going to be different in the coming years as
disruption is on its initiation. AI and Machine
learning are impacting digital
transformation and it is becoming crucial for
every business to bend its way of doing
business towards Data science for it to
survive. As the field of Data science grows,
every day, some factors are shaping all
these changes we are seen and yet to see.

4. Real-Time or in-memory
computing
There is a need to do everything in real-time, which is doing real-time
data analysis to improve on decision making. Large companies are
noticing the effects of making a decision fast, therefore, this is fueling
demand to have Data Science technology that can be able to have in-
memory computing.
In-memory computing allows data to be processed without getting
stored in the hard-disk of a computer. This is the ability to process
everything in memory without storing the data and later accessing it
for processing. This wastes time, therefore, for a better time saving, in-
memory computing can be used to make sure that everything is done
in a flash of a second, deciding in a real-time. The quicker a company
analyses data, the better it will be and more competitive it will
become.

5. Containers and hybrid
clouds
Data environments are becoming flexible and capable
of being transferred to where the business demand is.
Cloud and containers are shaping the future of Data
science completely by having the ability to scale
computing across the data centers and public cloud.
This happens without changing applications and is
helping developers become more creative and
ambitious in what they do. There is an increase in
teamwork, coordination, and working together, with
the use of containers and hybrid clouds. With the
hybrid cloud data management and IT department can
satisfy any demand without having a lift or sifting data.
Investments are data centers is helping companies
and bring more benefits as cloud help in integration in
data management.

6. Database as a
service
As cloud computing is becoming more relevant to
every organization and its benefits are being
witnessed, most companies are beginning to
consume databases as a service to capture the
befits of cloud computing. One of the befits of using
a Database as a service will be an operational cost
that most companies have, like having a database
expert which is costly. Therefore, outsourcing this
by having it as a service, will make a great impact on
the company.

7. Innovations like the
Internet of Things (IoT)
Innovations like the Internet of Things are shaping the way
Data Science works. All the devices that are connected to
the Internet are sharing resources. This has dramatically
shaped the way Data Science works. A lot of data and
information is available for use due to the use of IoT.
Therefore, the Internet of Things will make data science
work smoothly with easily accessible data, which is better
prepared and freshly generated. IoT is dealing with complex
data, which is giving better results, helping in making an
informed decision.

8. Blockchain
technology
The future is promising, that’s for a fact. The use of blockchain technology will bring a
new refreshment in a whole new way. The way data is stored, shared, and protected
is being revolutionized by the use of blockchain technology. Therefore, this
technology is shaping Data Science day by day as this technology is growing and most
experts are getting to understand the way it works. The Blockchain is ensuring trust
by maintaining the decentralized ledger. Both blockchains will impact Data Science by
controlling erroneous data by making sure it’s clean and is not duplicated. In addition,
Blockchain will ensure that the data is secure and will maintain its privacy, protecting
it from cyberattacks and any other security breaches that can occur on the internet.
Therefore, blockchain will be there to validate larger amounts of data for data science
to analyze and predictions from reliable information.

9. Blockchain is a game-changer. This technology
is a problem solver as it will be able to make sure
all the decentralized and centralized data is
validated. Furthermore, Blockchain integrates
well with other technologies like cloud
computing, AI, the Internet of Things (IoT), and
many others, making it highly useful to the field
of Data Science.
Data science will continue to be shaped by the
advancement in technology and innovations
that make it more productive. With the use of
new technology, it will be able to more informed
decisions in real-time causing a great impact on
the business environments.

10. Thank You