User Manual

> White Paper | Best Practices in Digital Transformation
3
u So, what does digital transformation mean for MTDCs? The
impacts will be far reaching in terms of changed requirements and
expectations customers have for more demand-driven, scalable
and ecient infrastructure that operates on the basis of intelligent
management and real time modeling, where the company and the
partners it may need to bring in are synchronized around data and
analytics.
The Internet of Things & the MTDC
Dealing with IoT and capitalising on the opportunities it presents
is a core element of digital transformation for MTDCs if they can
eectively harness it, since it oers insight that can transform the
way employees, suppliers, customers, products and processes are
understood and how facilities are designed and operated.
IoT is a key part of digital transformation. For the MTDC it will extend
the knowledge of and interaction with clients and lead to more
eective decision making in relation to them. It will also facilitate
that process in relation to external links into the data center such as
networks and other components of a client’s data infrastructure if
the MTDC is to act as the core control point of that infrastructure.
The situations in which IoT can be of greatest value to the data
center will reflect the previously stated transformation strategy and
include operations, CRM, business development, infrastructure
utilization, virtualization, capacity planning, operating systems
and data products. Depending on the business opportunity to
be realised, an MTDC may need to implement a number of IoT
technologies and strategies.
The deployment of IoT will require sensors at the point where data
is collected, sensor technology to manage and direct the sensors,
RFID tags, embedded systems technology, IoT analytics and the
means of acting on the findings.
The need to capture, process, store and analyse data to generate
corporate value has generated the emergence of a new breed of
technologies. Critical to the process of using IoT are two main
categories of technology – for storage given the huge amount of
data involved, and processing.
Ecient use of IoT in this context requires the data source to
be defined. All elements of the MTDC including infrastructure,
IT, storage, networks and security may be relevant data sources
to examine. Each of them provides valuable information for
understanding the performance of infrastructure and enables
infrastructure to be optimised. Ultimately, machine and software
data is the key to unlocking analytic applications.
In addition to the operational deployment of IoT, since the data
center is the source of business rather than just the enabler and
the clients are inside the facility rather than outside, so the IoT
needs to be related back to individual customer, budgetary and
contractual objectives.
Analytics
Analytics is the extensive use of data, statistical and quantitative
analysis, explanatory and predictive models, and fact-based
management to drive decisions and actions. Analytics can be
the input used for human decision-making or it may drive fully
automated decisions. In short, analytics enables decision-making
based on data and evidence, rather than speculation and ‘hunch’.
Analytics is important because data on its own is simply a set of
numbers, words, images, sounds or other symbols. Data itself needs
to be transformed to be able to be useful.
There are many benefits of deploying analytics for IoT within
the data center. These are linked with the reasons for deploying
IoT since analytics forms the processing component of the data
generated by IoT. The benefits can be described in terms of the
evolution of strategy through dierent types of analysis including
description, diagnosis, prediction, prescription and prevention.
MTDCs need a structured, actionable path toward optimising
their facilities in terms of business objectives by leveraging data
and analytics for their decision-making. That means defining
specific objectives based on corporate requirements, determining
the scope of the analytics strategy, creating a team of experts,
defining an improvement process methodology, and selecting
and implementing the right tools, technologies and data
integration methodologies.
The scarcity of data related to the data center will no longer be
the characteristic that defines MTDC eorts to understand their
data centers. There are significant issues that accompany the
deployment of analytics and which determine its use in future
decision making, whether human or AI-based including data
generation, data quality and reliability, data curation, data capture,
processing and storage.
The whole process leading to analytics requires the company
to identify the clear business goals that drive their data center
management. Analytics will necessarily be a long term strategy.
The application of analytics provides the opportunity of continuous
improvement in the MTDC data center in all aspects. In a
traditionally facility-oriented organisation, the IT department is
going to need more employees, not fewer. Big data analytics
requires a new breed of experts in the DevOps team, namely a data
scientist. u