According to IDC, worldwide revenues for big data and business analytics will grow more than $203 billion by 2020. One of the biggest challenges faced by anyone venturing into big data is the transformation of raw data into insightful information. By 2025, we’d be generating 180 Zettabytes of data per year and much of this data will come from IoT. The advancements in IoT will be a major factor for the growth in big data. Since data is growing in size along with the variety of applications and business use cases, the coming years are definitely going to be eventful in the big data space. Here are some of the trends that we are likely to see in big data during 2018.
Prescriptive analytics helps provide the right solution at the right time, in the right context. Big data will play a crucial role in facilitating prescriptive analytics in 2018. With its combined powers from analytics and mathematics, prescriptive analytics can help entrepreneurs make better decisions, leading to optimal production levels and enhanced customer experience. Cognitive computing combined with analytics can take big data to the next level and create ripples across the business world.
Historical data is often still left to be digitized and this is a major roadblock for those trying to harness the potential of this dark data. Data that was physically logged before the computer era still holds value when it comes to predictive analytics and many other data analysis methodologies. In 2018, along with the rise of big data, there will be significant efforts towards the recovery and digitization of historical data which remains in the dark. The revelation of historical data won’t happen overnight, but the benefits of having it is worth the wait as it can help make accurate predictions for the future.
Big data, as the name suggests has been more about the quantity than quality until now. When we talk about the sheer amount of data that’s available out there, it presents a challenge along with the opportunity. The issue here is to determine what data to focus on and what to ignore. This is important as focusing on the wrong datasets wouldn’t yield the expected results for your particular business need and further lead you to confusion and bad decisions. Datasets can be irrelevant to your use case, inaccurate, or even corrupted due to improper data acquisition methods. This issue is already being discussed by the industry experts and 2018 is likely to focus on data quality apart from the quantity alone.
The big data industry thrives on technological innovation and this is what helps businesses build great relationships with their customers. When it comes to data handling and security, the scene is not very mature right now. In the coming years, security of data is going to be a major concern for the customers and businesses will be forced to act responsibly and take the necessary steps to secure the data from security breaches. If your customers don’t trust you with their data, your brand engagement is going to suffer badly. Data security will be a prime concern for all companies in 2018 and it’s already high time to invest in tackling this challenge.
IoT devices have opened up a host of new data streams and this brings with it insights that never existed before. IoT will be the crux of big data analysis in 2018. With the increasing number of IoT devices, businesses have already started investing more in data aggregation from these devices. The benefits of such analyses is not just limited to businesses: consumers have equally benefited from the optimization of resources which has become possible with sensor data. Irrespective of industry and domain, almost all businesses will start reaping benefits from these new data sources in 2018.
As the digital revolution has transformed every organization into a technology organization, the increasing value of big data would force companies to adapt in certain ways. Businesses will have to implement the necessary tools to handle various stages of big data analytics. On top of this, skilled experts from the field of data science should be hired to handle various stages in the data pipeline such as extraction, transformation, loading , analytics etc. With this demand for experienced data professionals, IBM projects the job market for big data professionals will grow during 2018 from 364,000 openings to 2,720,000 by 2020.
Data assets are already being valued high by most business organizations. Cutting down the operational cost of various business processes is one of the top applications of data. This way, the returns from big data analytics is becoming easy to track. Newer big data tools come with advanced real-time data processing capabilities and this has made it easier to assign a monetary value to the data acquisition efforts. With this in place, data will be one of the hottest assets businesses would want to acquire in the near future.
BI tools such as Tableau continue to come up with new features like data certification to help skilled data professionals to achieve the desired business deliverables quickly along with layers of abstraction on top of the once complex data management process. The results of this are easily accessible documentation and metadata which will be of great help to non-technical business stakeholders. Simply put, 2018 will be pivotal in the rise of analytics as a service.
Data humanism is the process of enriching the personal and unique nature of big data using data visualization. The primary aim is to convert big data into small data thus simplifying and making the data more human-friendly. This will further complement the efforts to focus on data quality rather than quantity. We’re in the midst of a big data explosion and the advancements in technologies for storing, processing and analyzing data at a much lower cost than before will help take this data revolution forward while making the results more easily consumable by everyone.
New and improved business intelligence tools are hitting the market every day to help businesses better understand their operations, competitors and consumers. Augmented reality, AI and machine learning will be integrated into big data analytics and the result would be a more efficient business and improved customer experience.
Cognitive technologies will help equip machines to do tasks that require intelligence similar to humans. With the quantity of data rising, achieving this feat becomes easier. We will soon see machines handling tasks that need human cognition like handwriting recognition, face recognition, strategizing, reasoning and learning. Big data will drive innovations in this front and 2018 is likely to witness remarkable progress.
Machine learning is growing at a lightning pace and this would mean that we will soon be able to process and analyze huge amounts of data at a much faster speed and deliver more accurate results. The growth in this domain is driven by enormous amounts of data, refined algorithms and superior hardware. The processes will be more streamlined in 2018 and machine learning technologies will handle tasks like real-time ads, fraud detection and data analysis.
Big data is all set to remain a happening space in 2018 and the emerging trends support this claim. From cognitive technologies that can be used to retrieve dark data, big data will help prevent security breaches, fraud and help businesses achieve higher efficiencies and growth. Let’s hope these advancements and trends help the technology become more accessible and secure.