Digital transformation is increasingly becoming the focus for many CIOs around the world today—with analytics playing a fundamental role in driving the future of the digital economy.

While data is important to every business, it is necessary for businesses to have a firm grip on data analytics to allow them transform raw pieces of data into important insights. However, unlike the current trends in business intelligence—which is centred around data visualization—the future of data analytics would encompass a more contextual experience.

“The known data analytics development cycle is described in stages: from descriptive (what happened) to diagnostic (why did it happen), to discovery (what can we learn from it), to predictive (what is likely to happen), and, finally, to prescriptive analytics (what action is the best to take),” said Maurice op het Veld is a partner at KPMG Advisory in a report.

“Another way of looking at this is that data analytics initially “supported” the decision-making process but is now enabling “better” decisions than we can make on our own.”

Here are some of the current trends that arealready shaping the future of data analytics in individuals and businesses.

1. Growth in mobile devices

With the number of mobile devices expanding to include watches, digital personal assistants, smartphones, smart glasses, in-car displays, to even video gaming systems, the final consumption plays a key role on the level of impact analytics can deliver.

Previously, most information consumers accessed were on a computer with sufficient room to view tables, charts and graphs filled with data, now, most consumers require information delivered in a format well optimized for whatever device they are currently viewing it on.

Therefore, the content must be personalized to fit the features of the user’s device and not just the user alone.

2. Continuous Analytics

More and more businesses are relying on the Internet of Things (IoT) and their respective streaming data—which in turn shortens the time it takes to capture, analyze and react to the information gathered. Therefore, while analytics programspreviously were termed successful when results were delivered within days or weeks of processing, the future of analytics is bound to drastically reduce this benchmark to hours, minutes, seconds—and even milliseconds.

“All devices will be connected and exchange data within the “Internet of Things” and deliver enormous sets of data. Sensor data like location, weather, health, error messages, machine data, etc. will enable diagnostic and predictive analytics capabilities,” noted Maurice.

“We will be able to predict when machines will break down and plan maintenance repairs before it happens. Not only will this be cheaper, as you do not have to exchange supplies when it is not yet needed, but you can also increase uptime.”

3. Augmented Data Preparation

During the process of data preparation, machine learning automation will begin to augment data profiling and data quality, enrichment, modelling, cataloguing and metadata development.

Newer techniques would include supervised, unsupervised and reinforcement learning which is bound to enhance the entire data preparation process. In contrast to previous processes—which depended on rule-based approach to data transformation—this current trend would involve advanced machine learning processes that would evolve based on recent data to become more precise at responding to changes in data.

4. Augmented Data Discovery

Combined with the advancement in data preparation, a lot of these newer algorithms now allow information consumers to visualize and obtain relevant information within the data with more ease. Enhancements such as automatically revealing clusters, links, exceptions, correlation and predictions with pieces of data, eliminate the need for end users to build data models or write algorithms themselves.

This new form of augmented data discovery will lead to an increase in the number of citizen data scientist—which include information users who, with the aid of augmented assistance can now identify and respond to various patterns in data faster and a more distributed model.

5. AugmentedData Science

It is important to note that the rise of citizen data scientist will not in any way eliminate the need for a data scientist who gathers and analyze data to discover profitable opportunities for the growth of a business. However, as these data scientists give room for citizen data scientists to perform the easier tasks, their overall analysis becomes more challenging and equally valuable to the business.

As time goes by, machine learning would be applied in other areas such as feature and model selection. This would free up some of the tasks performed by data scientist and allow them focus on the most important part of their job, which is to identify specific patterns in the data that can potentially transform business operations and ultimately increase revenue.

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The Arctic is expected to get warmer and wetter by the end of this century and new research says that could mean trouble for infrastructure in Inuvik.

The study from Global Water Futures looked at how climate change could impact Havipak Creek — which crosses the Dempster Highway in Inuvik, N.W.T. — and it predicts some major water changes.

“They were quite distressing,” John Pomeroy, director of Global Water Futures and the study’s lead author, said of the findings.

Researchers used a climate model and a hydrological model to predict future weather and climate patterns in the region. They also looked at data gathered from 1960 to the present. 

If greenhouse gas emissions continue at their current rate — which Pomeroy said they are on track to do — the study projects the region will be 6.1 C warmer by 2099 and precipitation, particularly rain, will increase by almost 40 per cent.

The study also found that the spring flood will be earlier and twice as large, and the permafrost will thaw an additional 25 centimetres. While the soil is expected to be wetter early in the summer, the study said it will be drier in late summer, meaning a higher risk of wildfires.

John Pomeroy is the director of Global Water Futures. (Erin Collins/CBC)

“The model’s painting kind of a different world than we’re living in right now for the Mackenzie Delta region,” Pomeroy said.

He noted these changes are not only expected for Havipak Creek, but also for “many, many creeks along the northern part of the Dempster [Highway].”

Pomeroy said the deeper permafrost thaw and a bigger spring flood could pose challenges for buildings, roads, culverts and crossings in the area that were designed with the 20th century climate in mind.

He said the projected growth of the snowpack and the spring flood are “of grave concern because that’s what washes out the Dempster [Highway] and damages infrastructure in the area.”

Culverts and bridges may have to be adjusted to allow room for greater stream flows, Pomeroy said. And building foundations that are dependent upon the ground staying frozen will have to be reinforced or redesigned.

Pomeroy said the ultimate solution is for humans to reduce greenhouse gas emissions.

“This study is the future we’re heading for, but it’s not the future we necessarily have if we can find a way to reduce those gases,” he said.  

“It’d be far smarter to get those emissions under control than to pay the terrible expenses for infrastructure and endangered safety of humans and destroyed ecosystems.”

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