Look to the Data Trends for 2022
The world is changing rapidly. Some trends are predictable because they’re based on fundamental economic, political, social, and technological changes that have been going on for a long time. Other trends are unpredictable. In either case, if you want your business to be successful in 2022, you need to look ahead and make some informed guesses about what the world will be like then.
What a year 2022 will be! We are incredibly excited to share with you the data trends for 2022. The world is changing faster than ever. Technology is evolving every day and it brings new changes to our lives. Here are some predictions about the future of data, what we can expect in the next years.
Big Data won’t be
Big data is a buzzword today. But by 2022, big data will become a commodity and its main users will be the consumers. The new buzzword will be data democratization.
Increasingly, consumers will have access to their own data and be able to monetize it directly. They will be able to decide how it is used, allowing them to get a share of the money generated from it.
In 2022, people will no longer say “Please send me more information on that topic” or “I’m not interested in that anymore”. Instead, they’ll say: “That’s personal information about me, and I don’t want it to be used for that purpose.”
Data-driven decision-making is going to become a norm in life. As more decisions are based on personal data, people will demand a greater say in the process. This shift of power from companies to individuals will alter their relationship. Not only will individuals’ privacy become more protected than ever before, but they’ll take much more responsibility for their own health care and finances.
will get Personal
Predictive analytics is a field in which stats, science and technology meet to predict the future. In the past, it was mainly used by big companies who spent a lot of money on it. It’s not just about counting things any more. Predictive analytics is starting to get personal.
In 2022, predictive analytics will have moved from being a tool for businesses with deep pockets to a free application available to anyone with a smartphone or tablet. Thanks to cloud computing, which lets companies use remote servers for software applications, predictive analytics will become portable and accessible to everyone.
will get help from the crowd
Artificial intelligence, while still in its infancy, is already helping businesses make sense of the vast amounts of data they collect each day. But AI will soon get help from an unexpected source: the crowd.
The combination of artificial intelligence and the crowd is called “crowd AI,” and it’s one of the 10 data trends for 2022 identified by Gartner, Inc., a leading technology research and advisory company.
“Crowd AI will enable business users to harness collective insights into patterns that are otherwise undetectable by traditional machine learning techniques,” said Stephen Prentice, vice president and distinguished analyst at Gartner. “As more companies recognize the value of this approach, businesses will increasingly tap into crowdsourced data to augment their traditional internal data sources.”
Gartner defines crowd AI as the aggregation of data assets contributed by individuals or organizations to create high-quality data assets for training machine-learning algorithms. The process involves collecting information from individuals who use their own devices or applications to capture real-time events that are then shared with other contributors. Contributors can be customers, suppliers or partners
will go beyond data wrangling
Data is becoming the most important asset of every company, and it will continue to play an increasingly important role in our society. Data is becoming our new currency. As more industries use data as a key business asset, data management will continue to be a major challenge. We’ll see more companies facing data management issues that are not caused by the volume of data but by its complexity. So beyond the ability to store, process, and manipulate huge amounts of data, we are going to need smarter ways to manage this wealth of information.
To manage the growing complexity of our data, data management tools need to mature. Data wrangling tools enable us to make sense of our data by enabling us to find patterns within it and discover how it can be used. However, even the most experienced data wrangler is unable to use all of their data given its sheer size and complexity. The next step will be adding smarts into these tools so that they can help us discover insights in our data with limited human intervention.
We are already seeing how machine learning can have a positive impact on data wrangling tasks, such as cleansing email addresses from text or detecting events in social media posts. Using machine learning to extend what our existing tools are capable of is one way to manage the increasing complexity.
will enter our homes
By 2022, five billion connected things will be installed in homes, up from 10 million connected devices in 2000.
This 22-fold increase in connected home devices will have a profound impact on the way consumers live. The trend has already started. For example, smart TVs collect users’ viewing habits and search histories to deliver highly targeted ads.
Home appliances are also becoming smarter, with the latest models including self-cleaning functions or apps that connect you to service providers for remote maintenance. According to research company Gartner, 46% of companies are now using IoT technology for predictive maintenance programs alone.
Considering that there are more than 20 billion household appliances worldwide, this is a massive opportunity for companies to leverage data to deliver great customer experiences.
The connectivity of everything will also lead to the emergence of the invisible home – a smart living environment where everything is connected and can be controlled remotely.
With this development, users will have unprecedented control over their houses, allowing them to monitor their energy use or check if they’ve left the oven or lights on before they leave the house. As well as saving money, this could help reduce CO2 emissions by reducing energy consumption. And with security alerts about burglars posted direct to users’ smartphones, the benefits are obvious too.
Data will continue to grow—that’s a given. But how it grows will have a big impact on what we can do with it. See a few examples of how data solutions are implemented here.