Every aspect of daily life is becoming increasingly dependent on data and information. Businesses, non-profit organizations, governments and individuals are utilizing data science and machine learning to process data, identify trends and increase productivity.
In 2017, deep learning and artificial intelligence were two of the most exciting trends in data science. Expect to see these and other areas of data science continue to take the world by storm in 2018.
1. Increased Use of the Hadoop and Spark Platforms
Big Data platforms such as Hadoop and Spark really rose to prominence in 2017, and expect them to become even more popular in 2018. Hadoop in particular is able to harvest and collate huge amounts of data, then redistribute it to low-cost servers that run in parallel.
Apache Spark is expected to be the fastest growing big data platform in 2018. In-memory analytics are making it possible to further develop its operating model, which should make the platform more efficient and effective than ever before. For instance, calculations can already be completed up to 100 times faster than on the Hadoop platform.
2. Content Creation by Artificial Intelligence
Content is already the undisputed master of online marketing, and this isn’t going to change anytime soon. What is changing, however, is the way that content is being created. Increasingly, original content is being mass-produced to keep websites updated and fresh. Amazon, Google and many other major platforms are already relying on AI for content — although the technology is still in its infancy. While humans are still needed to proofread content, the results are improving all the time.
Artificial intelligence has already been utilized to write basic articles, social media posts and other types of online content. In 2018, marketers will be relying on AI to create dynamic content more than ever before. Specialist tools and software packages analyze the marketing requirements of a business, and create content according to relevant keywords and phrases. Automatically original and free from duplication, the content created by this relatively new technology has the potential to slash the marketing costs of multinational corporations.
3. Widespread Use of Deep Learning Technology
Until recently, Deep Learning technology was restricted to only the biggest and richest corporations and governments. Language processing methods such as machine translation, object classification and facial recognition will become mainstream in 2018 thanks to major improvements to artificial intelligence.
As businesses of all sizes gain access to increasingly powerful hardware, they too will be able to access Deep Learning technologies through the likes of Deeplearning4j and TensorFlow. And, as research continues, expect to see new and even more powerful technologies introduced to the market.
4. More Predictive Analytics in the Cloud
Companies of all sizes will continue moving their prediction analytics software to the cloud in 2018. Modern businesses rely on remote collaboration and flexible working with increasing frequency, and moving Big Data applications to the cloud makes these processes easier to implement and manage.
Some of the world’s biggest cloud computing providers are now starting to develop their own analytical services, allowing smaller companies to take advantage of machine learning technology without the need for significant capital expenditure. 2018 will be the year that these technologies finally become accessible to the masses.
This move toward a cloud-based approach to data science will make the traditional IT department in businesses increasingly redundant. Accessing applications using cloud-based technologies is easier and faster than ever, giving more marketers and sales professionals direct access to the insights they need.
5. Increased Use of Augmented Analytics
The way businesses, governments and organizations interact with analytical software is constantly evolving — and 2018 is expected to be the year of augmented analytics. This concept refers to the combined use of several data processes in order to deliver simple answers that are specific and actionable. Among the individual processes involved are augmented machine learning, augmented data discovery and augmented data preparation.
In reality, augmented analytics makes identifying trends a lot easier. For example, instead of entering several search criteria to get the answers you need, augmented analytics could give you the option of submitting a verbal query. This reduces the time it takes to find answers, which ultimately cuts costs.
6. The Internet of Things Will Expand
The Internet of Things is expected to grow significantly in 2018. An increasing number of businesses and individuals will be relying on internet-connected devices — other than computers and mobile devices — to make life easier. Refrigerators, lighting, security cameras, televisions and many other everyday items are gradually being connected to the internet. As a result, there’ll be more data to analyze in 2018 than ever before.
Big Data firms are now using the Internet of Things (IoT) to gain new and in-depth insights into a variety of markets and industries. And it won’t be long before the IoT has serious money-making potential for data science companies.
Data science is all about turning raw statistics into insight that can be used to improve the efficiency of organizations. Right now, it’s still up to humans to interpret these analytical insights — but 2018 could be the year when all that starts to change.