As
organisations begin their digital transformation journey, big data and
analytics can play a key role in it being a success
Big
data and analytics are topics firmly embedded in our business dialogue. The
amount of data we’re now generating is astonishing. Cisco predicts that annual
global IP traffic will reach 3.3 ZB per year by 2021 and that the number of
devices connected to IP networks will be more than three times the global
population by 2021, while Gartner predicts $2.5M per minute in IoT spending and
1M new IoT devices will be sold every hour by 2021. It’s testament to the speed
with which digital connectivity is changing the lives of people all over the
world.
Data has also evolved dramatically in recent years, in type,
volume, and velocity – with its rapid evolution attributed to the widespread
digitisation of business processes globally. Data has become the new business
currency and its further rapid increase will be key to the transformation and
growth of enterprises globally, and the advancement of employees, ‘the digital
natives’.
The Cisco Global Cloud Index points to the Cloud as the top
driver as exponential data centre growth with cloud centre traffic quadrupling
in the next five years. Data generated by IoT applications (such as connected
homes, smart cities and healthcare) will be 600ZB (zettabytes) per year by
2020, 39 times higher than current data centre traffic which is 15.3 ZB.
Big
Data therefore has a far-reaching impact and meaning. But how do we
understand it and its benefits, along with analytics on the journey to Digital
Transformation? Understanding the value of Data is key to the successful
implementation of operational strategies that facilitate agile and effective
business growth.
Big data means better business
Data is an enabler of future strategies and immediate
change, thanks to the power of predictive analytics and advanced data science.
Correctly harnessing data can help to achieve better, fact-based
decision-making and improve the overall customer experience. By using new Big
Data technologies, organisations can answer questions in seconds rather than
days, and in days rather than months. This acceleration allows businesses to
enable the type of quick reactions to key business questions and challenges
that can build competitive advantage and improve performance, and provide
answers for complex problems or questions that have resisted analysis.
Big
Data and analytics are becoming closely intertwined and need to work
together to deliver the promised results of Big Data. Traditionally, Data
management and analytics have resided in different parts of the organisation.
Breaking down organisational boundaries and creating better integration between
the IT and business departments is a critical step on the road to successful
transformation.
There is also a widespread realisation of the need for
better Business
Analytics (BI).Business Analytics are the skills, technologies, practices
for continuous iterative exploration and investigation of past business
performance to gain insight and drive business planning. The key is integrating
Big Data with traditional Business Analytics to create a data ecosystem that
allows the business to generate new insights while executing on what it already
knows.
Keep learning. Skills
are everything.
Proficiency with data mining and visualisation tools ranks
as one of the most important skills in determining project success.
All organisations need to consistently develop new data
mining skills to fully realise the business potential. A key trend in big data
is machine learning. Big data experts who can harness machine learning
technology to build and train predictive analytic apps such as classification,
recommendation, and personalisation systems are in high demand. Statistical and
Quantitative Analysis, which aims to understand or predict behaviour or events
through the use of mathematical measurements and calculations, statistical
modelling and research, is also imperative to accomplishment. Other key data
mining techniques that are employed industry wide include:
- Association - one of the best-known data mining techniques. With association, a pattern is discovered based on a relationship between items in the same transaction.
- Classification is a classic data mining technique based on machine learning.
- Clustering is a data mining technique that makes a meaningful or useful cluster of objects which have similar characteristics using the automatic technique.
- Prediction is one of a data mining techniques that discovers the relationship between independent variables and relationship between dependent and independent variables.
- Sequential patterns analysis seeks to discover or identify similar patterns, regular events or trends in transaction data over a business period.
- Decision tree technique; the root of the decision tree is a simple question or condition that has multiple answers.
Educate your
stakeholders
All stakeholders need to be educated and made aware of
Data’s value and understand that it’s essential to business continuity and
growth. But they may feel overwhelmed (and under informed) to the power and
complexity of the data if it is not properly communicated and presented.
Regular meetings, ideally face to face will enforce the importance of the issue
and the need for their buy-in.
Deliver Digital Ready
networks – it makes financial sense
All today’s businesses must, via Network Function
Virtualisation (decreasing the amount of proprietary hardware needed to launch
and operate network services), and Software Defined Networking (that allows
updates to be made in real time or as the business demands, in just a few
clicks) deliver Digital Ready networks to gain competitive advantage.
The increased simplicity and reduced costs associated with
deploying and maintaining a more digital-ready network are core benefits and
therefore should be employed as a necessity to improve and enhance business
efficiency.
Automation is a high
priority
Automation is a high priority in accelerating Digital
Transformation, allowing organisations to optimise their existing processes.
Automation technology is IT system and process agnostic, allowing businesses to
build on their systems within the existing IT environment.
In order to create a transformative environment and improve
speed and quality of delivery, organisations need to integrate automation into
their existing processes to increase the ability to frequently release
high-quality products - and to enable revenue and profit growth.
Automation also improves operational efficiency and allows
employees to focus on more rewarding tasks. With automation, cost-effective
solutions are enabled for repetitive, rules-based tasks. In addition, the
prospect of human error is eliminated, delivering outcomes that are 100%
accurate. By automating tasks, companies can significantly reduce the overall
process cycle.
The road towards digital transformation is a business
critical one. Organisations embarking on this journey need to consider how each
aspect of their business can be optimised to fulfil new digital objectives and
new growth potential. Big data and
analytics play a pivotal role in digital transformation, enabling organisations
to optimise their existing processes and stay ahead of the competition.
Source: ITproportal
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