The future of data lies in analytics

November 7, 2018

By Senior Manager Evangelos Tzimopoulos

The ongoing proliferation of data – total worldwide data is predicted to grow ten-fold over the next seven years – brings a raft of opportunities and challenges. Embraced properly, it will provide immeasurable benefits for companies in multiple markets and the potential for transformation is vast. The key however is to embrace the change, and with the help of analytics, machine learning and Artificial Intelligence (AI), learn how to use it to your advantage.

This is however not a simple task. Fully embracing the opportunities requires not only the acknowledgement of the opportunities themselves, but also a series of complex governance and technology decisions built around a comprehensive data management and governance strategy. Without this framework, a business will struggle to embrace the changes.

Core disrupters of the digital age

Data technologies have emerged as one of the core disrupters of the digital age and analytics, defined as the discovery, interpretation and communication of meaningful patterns in data, is one of those. Analytics has become the new ‘go to’ competency within the business world, and data scientists are today’s pioneers, leading the way. As well as creating opportunities, the developments also pose challenges in terms of disruption not only to the existing landscape, but also to organisations, their culture, structure and the skills required for them to succeed going forward.

To address these issues, let us take a look at the three main developments that have transformed how organisations look and use data:

  1. the exponential growth of data,
  2. the proliferation of high-powered analytics tools and machine learning to analyse the data by non-subject matter experts, and
  3. the use of the cloud as a distribution mechanism.

The explosion of data has created new possibilities which impact not only how data is stored and processed, but also the intrinsic value of the data and the insights that can be pulled from this data.

Moreover, the use of new high-powered tools is changing how firms use analytics, moving away from summary or descriptive processes to planning, prediction, calculation and optimisation features made possible through machine learning.

Advanced analytics platforms

The advance of modern computing, the inexpensive hardware, and the availability of low-cost and distributed storage (the cloud) has allowed the development of data engineering tools and advanced analytics platforms that bring all these capabilities together to provide an all-inclusive ecosystem that can host, process and extract new value from (big) data.

As already mentioned however, transforming your organisation into one that is at the forefront of transformational data analytics is not easy. Data governance is a critical pillar in any big data or analytics programme as it helps prevent organisations opening themselves up to risk, such as data breaches, unsustainable data models and onboarding data that is never used. There are many things to consider when devising an appropriate governance framework, with the main three issues being data security and compliance, the team, and data quality.

Security and privacy issues

Collecting and storing vast amounts of data creates many security and privacy issues, making big data and data analytics a prime concern for IT security personnel at banks. The addition of cloud-based storage and distribution, with big data analytics layers, only serves to heighten these threats further. Another part of the challenge is that most data security systems are designed to work on small amounts of data and cannot be adapted for big data volumes.

Traditionally, access to data stores has focused on use-case management, but the lack of consistent categorisation often leads to misuse. Going forward, good transformational analytics governance will need to focus on data management rather than use-case management.

Enable and not restrict analytics

In addition, to fully realise the benefits of transformational analytics, data and analytics tools must be made available as widely as possible across the business. Not only data scientists, but business users and other technologists must be able to experiment with data to accelerate the discovery of critical business insights. The key is to enable and not restrict analytics. Show the users how to access the analytics tools, rather than tell them what they can’t do. By enabling, rather than impeding, the data governance programme will be seen as a partner to get the right data to the right user, rather than a system to be worked around.

While the areas of analytics and data science have come a long way over the past few years, with more organisations using the domains to aid their strategic decision making, the potential is still vast. Significant amounts of time and money are being invested in the sector, with new technologies and methodologies emerging constantly. Ignoring these opportunities could be fatal for your business. Embrace the changes now and reap the benefits in all areas of your business.


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