Big Data Trends to Watch in 2018

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In 2018, the use of Big Data in general and AI specifically is expected to continue, most likely at an accelerated pace

The use of Big Data continues to grow across all industries, with innovations in data analysis continuing to improve strategic business decisions.

The introduction of machine learning and artificial intelligence (AI) is making implementation of data driven strategies happen faster. Both are used to automate routine tasks in data collection, as well as allow for much faster analysis and interpretation of large datasets.

In 2018, the use of AI specifically is expected to continue, most likely at an accelerated pace. Here are some of the Big Data trends to watch out for as the second decade of the 21st century moves into its final years.

Analytics

As AI and machine learning continue to become integrated with data collection and analysis, more changes will happen in how humans interface with data. For example, according to a new report from Forrester Research:

  • 25% of businesses will use conversational interfaces to supplement point-and-click analytics. With such interfaces, humans can query analytics applications using natural language and get immediate answers that include data visualizations.
  • 33% of organizations will “unplug” the funding for their older data lakes because they are not adding value to the business. Data lakes are huge repositories of data that has not been cleaned, de-duplicated or structured.

The use of AI-driven prescriptive analytics also should increase. This type of analytics involves taking all the available data and offering recommendations in real-time for the action that will most likely lead to success. Basically, prescriptive analytics involves getting the right answer at the right time.

AI and Machine Learning

According to the Forrester Research report, about 20% of organizations will use AI to provide real-time, actionable recommendations from data and leverage this to make decisions. This could include a variety of issues, from what products and services to offer customers to recommended terms to offer suppliers.

Forrester also projects that AI will help to analyze the many terabytes of older data that some companies have stored, providing further insights for decision-making and overall strategy.

AI is expected to play a role in improved cyber security as well (including the ability to use data to anticipate future attacks) and is key to the success of prescriptive analytics.

Machine learning involves automating processes. Once taught the initial task through coding imputed by humans, machines can learn how to handle related tasks over time. Expect the learning time for machines to accelerate in 2018, with a heightened ability to analyze large sets of data and come up with even more accurate results.

Insights as a Service

A focus on lower costs and more flexibility with software will also drive many businesses to contract with cloud-based analytics services for data storage and analysis. This includes insights as a service, or having an outside vender offer recommendations based on data analysis, often involving AI.

Forrester Research expects 80% of businesses will turn to outside consultants for some portion of their insights capabilities in the coming year.

IoT

The Internet of Things (IoT) is impacting Big Data and the industries that use it in a significant way. IoT essentially involves placing sensors on objects in the real world and collecting data. This can range from cattle farmers trying to track illness in their herds to retails stores trying to optimize their ecommerce efforts.

IoT is also key to self-driving cars, as sensors on the cars connect and share information with sensors on other cars as well as object along the road, such as traffic signs.

Expect IoT applications to become more specialized as engineers move away from pure experimentation and more into building platforms for specific industries.

Blockchain

Blockchain is a potentially disruptive innovation. It’s the software application that allows for transactions using cyber-currency such as Bitcoin.

In its look ahead at 2018, Dimension Data said blockchain could become disruptive to “companies that have not started the digital investment cycle in blockchain, AI, machine learning, robotics, VR {virtual reality] and AR [augmented reality].”

Blockchain technology could prove especially important in combination with IoT. The blockchain technology can handle millions of small transactions. That type of technology can work with IoT, in which sensors are generating millions of “transactions” – i.e. communications with other sensors.

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