2017: What do Big data, cloud, self-service and machine learning have in common?

2017 is set to be a very exciting year for the technology industry and data analytics is going to see huge growth.

Big data has finally come of age and interest in the analytics industry has never been keener. The sums invested in big data analytics continue to increase every year. According to a recent IDC report, the big data and business analytics industry saw revenues of $130 billion in 2016 and is forecast to continue to grow, with estimates that it will reach $203 billion by 2020.   2017 will largely be a consolidation year for the core proposition of big data analytics, but it is a young industry and the effects of better data analytics are now beginning to spill into other related fields.  

This is where the big changes will occur in 2017. As analytics continues to improve, the changes it initiates will impact wider areas such as cloud-based Analytics-as-a-Service, Business Intelligence, the Internet of Things and Machine Learning.

Deployment of cloud-based analytics will rapidly accelerate in 2017

In recent years, cloud adoption has moved from a niche proposition and into the mainstream. It is now becoming the norm for many businesses and the benefits are clearly understood. Looking ahead to 2017, the cloud will continue to be adopted by businesses of all shapes and sizes, irrespective of the market segments that they are active in – that is a given. However, what will change in 2017 is that cloud adoption will move beyond its staple of replacing infrastructure and software solutions; cloud adoption will move into data analytics as cloud-based analytics solutions mature, gain features and become attractive to businesses.

The next buzzword in the cloud will therefore be Analytics-as-a-Service (AaaS). Instead of running analytics on premise, a complete Analytics solution will become a service at an operational cost, not a capital one.

Analytics in the cloud is beneficial for businesses both large and small. Startups will be able to start small with their analytics in the cloud and then expand as they as grow, matching the capabilities of larger competitors. Conversely, enterprises can scale back their solution if their business strategy changes and gain from additional enterprise-level features as they are rolled out. Moreover, both business types will have the ability to elastically use more compute power as and when it is necessary for complex analysis, and then go back to standard compute levels for everyday analysis.


Business users will use self-service business intelligence tools

Through 2017, the business intelligence and reporting layer will become easier to use and will begin to be geared towards self-service for business users.

As data analytics integrates itself further into the core of the business, there will be a shift towards the business diving into data analytics by combining software solutions. With a database such as EXASOL, a data preparation tool such as Alteryx, and a visualisation tool such as Tableau, a complete “big data analytics stack” can be created that takes the time and complexity out of data analytics. This reduces business users’ reliance on data scientists and IT resources, allowing them to run self-service business intelligence reports.

The key to getting the most out of the data with minimal effort is finding the right combination of tools that work together to extract value. As more businesses bring together these components and use the right tool for the right job, self-service BI will accelerate throughout 2017.

The potential for the Internet of Things will be realised with smart cities and industrial automation 

2017 will be the year when the Internet of Things moves on from talking about “smart fridges.” To date, most of the hype has centred around smart devices and how the Internet of Things will have a great impact to the consumer, whether it be through smart homes, smart watches or smart cars. Despite our optimism, none of these have advanced as far as we expected, and we are still waiting for previous predictions surrounding smart devices to catch up to the hype.

However, businesses and governments are now realising the potential that the concept of IoT holds. Much of the value lies in the insights that can be gained from analysing the datasets they generate. Therefore, the biggest Internet of Things developments in 2017 will come from the growing interest in industrial automation and smart cities, rather than in smart devices. This means we will see a more concerted effort to fund research into these two areas and it is expected that consumer Internet of Things adoption will continue to lag behind the hype.

Machine learning and artificial intelligence becomes embedded within the database to drive predictive analytics

Machine learning and artificial intelligence came of age in 2016. Self-driving cars made huge strides in their development, the abilities of artificial intelligence fast-forwarded a decade with the Go world champion-beating bot, and artificially intelligent assistants entered our homes, listening to our every command. What underpins all these devices is data, and in some ways, 2016 could be considered the year that data was finally tamed for artificial intelligence.

2017 will move the artificial intelligence needle on from the consumer and into business, where it will be applied to help businesses reduce costs and improve customer satisfaction. Improvements will come with advancements such as embedding machine learning and AI directly into the database. This will mean that predictive analytics will thrive, with more advanced algorithms and better actionable insights. Prescriptive analytics will become widespread, prescribing the best course of action for a business, based on the data available. From retail to manufacturing and on to finance, artificial intelligence in business will be a big growth area in the coming year.

Conclusion

2017 is set to be a very exciting year for the technology industry and data analytics is going to see huge growth. The importance of data has finally been realised and, with the latest tools, it has been tamed and understood. As a result, areas such as artificial intelligence are improving faster than ever. Business intelligence tools are maturing and becoming easier to use. The best businesses have an opportunity to leverage these advancements in 2017 and outgrow their peers by using the tools that are at their disposal.

Aaron Auld, CEO, EXASOL AG
Image source: Shutterstock/wk1003mike