From artificial intelligence to small data, these are the top data and analytics trends that will help you grow your business in 2022.
Over the last several years, companies have embraced the underlying principles behind advanced analytics, beginning with buzzwords like big data to hot topics like machine learning and artificial intelligence. These technologies have attracted the attention of both IT professionals and company leaders, who realize their promise for everything from cost reduction to increased revenue, to speeding innovation and boosting market competitiveness. However, this promise can sometimes be overshadowed by the realities of adopting them in an enterprise scenario.
Big Data is becoming too big, resulting in data swamps that are difficult to implement. Finding the correct data in the right location, regardless of where it was produced, and ingesting it for data analytics is a game-changer since it saves time and human labor while giving more relevant insight. As a result, instead of Big Data, a new trend will be the creation of what is known as “right data analytics.”
With this in mind, it’s time to find new ways to collect unique data that unlock innovative insights.
Top Data and Analytics Trends for 2022:
1. Consumer Data
2. Product Data
3. Medical Data
4. Multilingual Data
5. Data Diversity
1. Consumer Data
Keep an eye on consumer trends and learn everything you can about a certain set of customers, including what they do, where they live, their age bracket, gender, and so on. Obtaining consumer reviews allows businesses to learn what customers are complaining about and what adjustments they are recommending, giving you a better understanding of who the ideal customer is and what qualities or attributes a product must-have.
Skincare, Haircare & Cosmetics Reviews
Learn why certain products are preferred over others and when they are typically purchased.
Consumer Packaged Goods (CPG) Reviews
Understand what customers think about a product and unveil its strengths and drawbacks.
Computer & Electronics Reviews
Know what made consumers choose a particular product and evaluate their post-purchase satisfaction.
Hotel & Restaurant Reviews
Discover what qualities guests appreciate the most and what matters in customer experience.
2. Product Data
By having a full dataset that includes what is being sold, for how much, product characteristics, sales volume, and so on, brands will be better equipped to identify new opportunities and buying trends, such as what consumers are losing interest in seeing on shelves and online stores. That is the main reason why product data is considered one of the top data and analytics trends for 2022.
Clothing
Have specific information about any clothing item available for your marketplace or research.
Auto Parts
Obtain a list of makes and models, their parts, or specific oils and lubricants over the years.
CPG
Enrich your product database with up-to-date information.
Tools & Equipment
Gather information about products in a specific industry or vertical.
Let’s Work Together
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3. Medical Data
Amid a pandemic, data analytics and artificial intelligence have taken an exceptionally robust stance in always obtaining the most trustworthy information. Apart from assisting in the research and development of innovative treatment processes, it presents an essential information source for COVID statistics, adverse events identification, drug information, and so on.
Adverse Events (AEs)
Evaluate any potential unexpected medical problem that arises during drug or other therapy treatment.
Drug Information
Know all about a particular medicine such as its composition, uses, side effects, or interactions.
4. Multilingual Data
For a long time, one of the key objectives of natural language processing researchers and developers has been to create a multilingual AI model that supports all languages, dialects, and modalities. Multilingual datasets are critical in achieving this objective. Access to multilingual or monolingual domain-specific datasets will become a major trend, especially as most companies are now attempting to engage with a much larger global audience, particularly through chatbots or voice-activated commands.
Sentences
Enrich your machine learning models with sentences from native speakers.
News
See what took place in multiple languages anywhere in the world within a given time period.
5. Data Diversity
Datasets can be diverse in types, including text, audio, picture, video, and so on, but also to eliminate bias in data. Text data is more common than all other types of datasets on the market. For example, points of interest (POI) related to transportation, food, and entertainment, or housing data with real estate listings and rental properties, can provide information about a specific location or a collection of similar locations that can help businesses drive better decisions. However, as user habits change as a result of highly digitalized everyday contexts, voice messages, commands, and images are increasingly becoming an important form of communication.
Points of Interest (POI)
Know the exact coordinates of businesses, governmental institutions, or public facilities.
Real Estate
Know what’s being sold, where it’s being sold, and how much it’s being sold for.
Voice Commands
Obtain commands for use in voice recognition interfaces, allowing for spoken human-computer interaction.
Images
Obtain images that are ready to be used in the creation of an ideal dataset for the machine learning algorithm.
Conclusion
With the emergence of marketplaces for nearly any type of data, from language data to geodata or marketing data, companies today have more direct access to the market than ever before. After reading the top data and analytics trends for 2022, it is clear that the future is undeniably more data-centric, more so than ever before.
However, data alone is not enough. Data still needs to be molded into a usable format; cleansed data; enriched data to get more meaning; and properly formatted data making it usable for analysis.
