Big Data analytics growth and the industrial internet

Big Data has made waves in the IT sector over the past few years, offering greatly increased capabilities in areas such as predictive analytics and understanding of niche trends.

In fact, a recent study conducted by GE and Accenture found there was a growing urgency for organisations to embrace Big Data analytics – specifically to advance industrial internet strategies. This is a term used to describe the integration of machinery with networked sensors and software, similar to the Internet of Things.

Big Data will need to become a serious part of IT strategies in the near future, if organisations hope to correctly manage this industrial internet trend. It's essential that appropriate considerations are made for the proper management and control of Big Data strategies.

Growth in Big Data analytics

Big Data is currently experiencing strong growth, as greater numbers of organisations begin to realise the benefits of adopting powerful analytics capabilities.

This can be seen in healthcare, in which around one third of surveyed organisations stated they were 'ahead of the game' when it came to analytics. This is according to the Accenture study, which also found around half to be increasing Big Data analytics investments from 10 to 20 per cent of technology budgets.

As analytics technologies becoming increasingly capable, businesses across a number of sectors will certainly want to consider the benefits. This is already being seen in the industrial sector, where companies are using Big Data analytics to handle equipment monitoring.

Big Data and the industrial internet

The industrial internet offers a new approach for enterprises needing to monitor equipment, but the sheer amount of data generated could prove difficult to handle. This is where Big Data is set to be essential, given the management capabilities of the trend.

According to the Accenture study, 65 per cent of companies are currently using Big Data analytics to handle equipment monitoring, but only 29 per cent of a surveyed 250 executives are using Big Data for predictive analytics. While correct monitoring and management of equipment is key, predictive analytics has a real capability to change businesses.

This is a technology that when correctly utilised can identify potential issues before they become larger problems, thus reducing any unnecessary strain on an organisation.

In terms of the industrial internet, it means power generation facilities like wind turbines or solar panel installations can gather and feed relevant information back to the enterprise. If any errors are identified, they are quickly understood and corrected. 

Correctly managing Big Data use

Big Data is a substantial undertaking, and will often mean far more data analysis than most companies are used to. It's in these instances where a management framework can be effectively utilised.

AGILE is one of these frameworks, and is especially useful for technology-focused project management (like Big Data). Once it has been implemented, there's more effective communication between staff and different teams, along with regular reviews of prioritisation and re-planning.

This flexibility is required on modern business projects, and can ensure that efforts never go too far off track.

ALC Training is one of the principle providers in the Asia Pacific of the AGILE framework, and businesses need to consider the value of these hosted courses.


Big Data will certainly continue to experience growth over the next few years, especially as enterprises begin to understand the performance capabilities and benefits. The industrial sector will likely become a centre of this Big Data development, as organisations use powerful analytics to manage power systems and other complex equipment.

Organisations will need to consider how to best integrate Big Data analytics, and take advantage of the appropriate management frameworks.