Big Data Trends You Should Know About in 2018
The term Big Data refers to the entirety of the process that information goes through for real-world application. This means that it encompasses data gathering, data analysis, and data implementation.
In this post, we’ll briefly cover how big data got to where it is today and analyze the big data trends you should know about in 2018. Knowing what to do in the midst of change will help you implement the right data-driven marketing strategies to future-proof your business.
The Evolution of Big Data
In the past, big data was used primarily by big businesses, not only because their broad scope of service demanded more precise data, but also because they were the only ones who could afford the technology and channels used to collect and analyze the information.
Much like any other process in the business world, Big Data has evolved at an unbelievably fast pace. The best example of this is Big Data in the cloud. Today, even small businesses can take advantage of Big Data, as the convoluted setup and costly data experts aren’t required anymore because everything they need can be accessed remotely.
In addition, both people and businesses are switching to a digital system, which in turn generates pools of information. Different forms of data are collected and connected to aid businesses in drawing analogies between datasets, coming up with actionable insights and helping them with decision-making.
The never-ending stream of information is incredibly useful for businesses, but it can also be a challenge to draw relevant insights from such a large data pool. Another problem is getting the right information. Even with these challenges, there’s no denying that Big Data offers business opportunities and growth.
2017 At a Glance
In 2016, security and privacy were major themes of concern for Big Data, and that spilled over into 2017, especially with numerous hacks and data breach scandals.
According to experts, Big Data also had a societal impact in the form of fake news recognition, coinciding with the misuse of social media platforms, as it could be used by propagandists to undermine democracy.
The cloud and the Internet-of-Things (IoT) were expected to play significant roles in the development of Big Data management and generation. Analytics show the real value of IoT, as it is being used to create IoT product offerings. There was also a shift to streaming/edge cloud architectures for more storage and analytic workloads, which allowed Big Data analytics to progress even further.
Other Big Data trends in 2017 are as follows:
- Big Data shifted from a departmental approach to business-driven data approach, with a focus on agility in the use of analytics capabilities, to drive short and long-term business value.
- Users steered toward alternative data stores that are better for their analytic workloads. More emphasis was given to data management, data visualization, and hybrid clouds.
- Advanced Analytics—Artificial Intelligence (AI), Deep Learning, and Machine Learning—became business differentiators driving Big Data maturation. Experts used them to make sense of the information and help derive value from the growing number of available information assets. Conversational AI (chatbots) took off as organizations adapted it to improve customer service.
- Variety became the most significant driver of Big Data investments, according to a survey by New Vantage Partners. Because of this, analytics platforms are able to facilitate connectivity from between a diverse range of sources.
1. Fast Growing IoT Networks
People can now control their humble home appliances through smartphones, all thanks to the concept of IoT. No one knows yet if gadgets like the Amazon Echo will be a mainstay in homes, but the involvement (and investment) of big companies means that businesses and consumers will continue to use internet-connected devices.
With more organizations launching IoT solutions, the growing IoT craze will help create more data and touchpoints for businesses to collect information. Many will also need new technologies and systems to manage and analyze the flood of big data coming in as a result.
For 2018 and beyond, responsive devices and smarter networks are what the market will be focusing on. With all the new devices coming online, there is also an expected increase in the growth of data collected. Expected total business expenditure towards IoT will be at $6 trillion by 2021, with a $15 trillion contribution to global GDP by 2030.
2. Artificial Intelligence is Becoming More Accessible
Companies, both large and small, are now utilizing AI functionalities like chatbots to automate specific processes. Since there are prebuilt AI applications now due to high demand, SMEs can easily get their hands on this technology, which levels the playing field for all. It’s now up to their Sales and Marketing teams on how to better utilize this technology.
3. Predictive Analytics is On the Rise
Analytics is now a substantial strategy for businesses to achieve their targets. Companies look at big data to see what happened and use their analytical tools to find out why those things happened. Predictive analysis uses big data to predict what might happen in the future.
No doubt that it will be useful for data-driven marketing, as it can help analyze data to predict consumer behavior, allowing Sales and Marketing teams to know a customer’s next action before they even take it. Analytics is also trying to provide more context to data to help understand the why behind the what.
Today, only 29% of organizations use predictive analytics, according to a survey from PwC. This number is expected to grow this year moving forward, as many vendors have recently come out with predictive analytics tools.
4. Dark Data in the Cloud
Dark data, or information that is yet to become available in digital format, is an untapped reservoir for now. In 2018, these analog databases will hopefully be digitized and put in the cloud so they can potentially increase the range of trends and cycles that businesses can predict.
5. CDOs are Stepping Up
With data becoming an integral business strategy, Chief Data Officers (CDOs) are becoming a more critical role in an organization.
In a Forbes survey, more than 50% of CDOs will likely report directly to the CEO in 2018. They’re bound to take on more active roles in shaping their businesses’ initiatives. This is good news for data marketers in a more personal sense, as this means there is room for career growth.
6. Quantum Computing
Imagine being able to crunch billions of numbers at once, in a matter of minutes. Such immensity and speed cut big data processing time by more than half, allowing companies to take action in a more timely manner for improved results.
Something this massive is only possible through quantum computing, which will likely be utilized soon as companies like Google, Intel, and the Turing Institute start actively developing and battery testing quantum computers.
7. Better, More Intelligent Security
Last year’s scandals are enough to make any enterprise paranoid about hacking and breaches, so in 2018 companies are focusing on fortifying data confidentiality. IoT is also a cause for concern with possibilities of cybersecurity issues. Big Data companies are now helping providers market products that use data analytics as a tool to detect and predict threats.
Big Data can be used as a security strategy. A security log data can provide information about past threats, which companies can use to prevent and mitigate future attempts. There are also those that can choose to integrate their security information and event management software with Big Data platforms.
8. Open Source
It’s likely that public data solutions like Apache Hadoop and Spark will continue to dominate. In 2017, enterprises expanded their use of Hadoop and NoSQL and looked for ways to speed up data processing. In 2018, technologies that allow access and response to data in real time will be in high demand.
Open source applications are no doubt cheaper and will cut costs for your business, but as with any other good thing, there are certain drawbacks that you should be aware of.
9. Edge Computing
With edge computing, the big data analysis happens not in the data center or cloud, but close to the IoT devices and sensors. For companies, this means better performance since there’s less data flowing in the network and fewer cloud computing costs.
Storage and infrastructure costs also decrease because the company can choose to delete irrelevant IoT data. Edge computing can also speed up data analysis, allowing for faster action times from decision-makers.
10. Chatbots will Get Smarter
In 2016, Facebook allowed developers to integrate chatbots in its Messenger service. Since then, many companies have deployed bots to take queries from customers, giving them a more personalized method of interaction without the need for human customer service personnel.
Big Data is the foundation of this customer experience, as bots process volumes of data to produce the most relevant answer based on keywords in the query. They’re also able to pick up and analyze information about customers based on a conversation.
The improvement of bot technology will help marketers collect more/better data to develop both their customer service strategy and targeting of online ads. It also helps businesses cut costs on support resources.
Things to Remember
The advancement you enjoy today in virtually every industry can all be traced to Big Data. It has helped create smarter cities, better academics, medical breakthroughs, and more efficient enterprise resource planning.
But for it to reach its full potential, you must thoroughly understand and use the right technology, skills, processes, planning, and industrial applications.
As it becomes more available and affordable to implement Big Data strategies, you can expect more changes and trends that will help your business grow and thrive.
To learn more about the different ways your business can use data to grow your sales funnel, be sure to check out our FREE whitepaper: The Complete Guide to Data-Driven Marketing