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Top 10 Big Data Trends For 2022

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  • Difficulty Level : Medium
  • Last Updated : 25 Jan, 2022

In today’s world, we are living in an era of a new digital world where Artificial Intelligence and Machine Learning have reshaped businesses and society. You might not be surprised that big data has taken over the perspective of seeing through new market trends and making important decisions for the business. In fact, with the growth of data, companies are now looking to adopt new methods to optimize data on a larger scale. Big data has also played a crucial role during the COVID-19 pandemic and has uplifted many sectors such as healthcare, e-commerce, etc.

Top-10-Big-Data-Trends-For-2022

It is being expected that the big data market is going to shoot up to 200 USD Billion by 2025. So, let’s check out the top 10 big data trends for 2022.  

1. TinyML

TinyML is a type or technique of ML that is powered with small and low-powered devices such as microcontrollers. The best part about TinyML is it runs on low latency at the edge of devices. Thus, it consumes microwatts or milliwatts which is 1000x less than a standard GPU. This quality of TinyML helps devices to run for a longer period of time which can also be years in some cases. Since they’re low on power consumption, they don’t allow any data to get stored and that’s the best part when it comes to safety concerns.

2. AutoML

It is also considered as modern ML these days. AutoML is being used to reduce human interaction and process all the tasks automatically to solve real-life problems. This functionality includes the whole process right from raw data to a final ML model. The motive of AutoML is to offer extensive learning techniques and models for non-experts in ML. Not to forget, although AutoML does not require human interaction that doesn’t mean that it’s going to completely overtake it. 

3. Data Fabric

Data Fabric has been in trend for a while now and will continue its dominance in the coming times. It’s an architecture and group of data services throughout the cloud environment. Not only this but data fabric has been also listed as the best analytical tool by Gartner. However, it has to continue spreading all over the enterprise scale. It consists of key data management technologies which include data pipelining, data integration, data governance, etc. It has been accepted by enterprise scales openly as it consumes less time for fetching out business insights which can be helpful for making impactful business decisions.

4. Cloud Migration

In today’s world of technology, businesses are now shifting towards cloud technology. However, cloud migration has been in trend for a while now and this is the next future in technology. Moving towards the cloud has several benefits and not only businesses but even “we” as an individual are also relying totally on cloud technology. Cloud migration is very much helpful in terms of performance as it uplifts the performance, speed, and scalability of any operation, especially during heavy traffic. 

5. Data Regulation

Since industries have started changing their working patterns and measuring business decisions, it’s now making it easy for them to manage their operations. However, big data is yet to make some more impact on the legal industry. In fact, some have started adopting big data structures but it’s a long way to go. This comes up with a lot of responsibility of handing data on such a large scale and some specific industries such as healthcare, legal fields cannot be compromised or let’s say if there’s any patient data, it cannot be left with AI methods only. So, as far as we’re concerned a better data regulations are going to play a major role in 2022.

6. IoT

With the growing pace of technology, we’re becoming more dependable on technology. IoT has been playing a great role in this for the last few years and we believe it’ll be playing a more interesting role in the near future. Today advanced data technologies and architectures are adding value over IoT with the help of monitoring, and collecting data in different forms. We believe IoT should be playing it on a larger scale now for storing and processing data in real-time to solve unusual problems such as Traffic Management, Manufacturing, Healthcare, etc.

7. NLP

Natural Language Processing is a kind of AI that helps in assessing text or voice inputs provided by humans. In short, it is being used nowadays to understand what’s being said and works like a charm. It is a next-level achievement in technology where we’ve been working now and even you can find some of the examples where you can ask a machine to read aloud for you. NLP uses a method of methodologies to extract the vagueness in speech and to provide it a natural touch. Your very best example can be Apple’s Siri or Google Assistant, where you speak to the AI and it provides you the useful information as per your need.

8. Data Quality

Data quality has one of the most sought concerns for companies later in 2021. In fact, the ratio is less where companies have accepted that data quality is becoming an issue for them. Well, on the other hand, it’s not a concern for them. To date, companies have not been focusing on the quality of data from various mining tools which resulted in poor data management. The reason is, if ‘Data’ is their decision-maker and playing a crucial role then they might be setting wrong targets for their business or might be targeting the wrong group. That’s where filtration is required to achieve real milestones.

9. Cyber Security

With the rise of pandemic (COVID-19), where the world was forced to shut down and companies were left with none other than WFH, things began changing. Even after so many months and years, people are focusing on getting remote work. Everything has pros and cons in its own way. This also comes with a lot of challenges which include cyber-attacks. In fact, working remotely comes with a lot of safety measures and responsibilities. Since the employee is out of cyber security range and thus it becomes a concern for companies. As people are working remotely, cyber attackers are becoming more active to breach out by finding different ways of attack. 

Taking this into considerations, XDR (Extended Detection and Response) and SOAR have been introduced which helps in detecting any cyber-attack by applying advanced security analytics into their network. Therefore, it is and will be one of the major trends for 2022 in big data and analytics.

10. Predictive Analytics

It helps in identifying any future trends and forecasts with the help of certain sets of statistics tools. Predictive analytics analyses a pattern in a meaningful way and it is being used for weather forecasts. However, its ability and techniques are not just limited to this, in fact, it can be used in sorting any data, and based on the pattern, it analyses the stats. 

Some of the examples are Share market, Product Research, etc. Based on the provided data, it measures and provide a full report beforehand if any market share is dipping down or if you want to launch any product then it collects data from different regions and based on their interests, it will help you in analyzing your business decision and in the world of this heavy competition, it’s becoming even more demanding and will be in trend for the upcoming years.

Conclusion

It’s not that difficult to understand how the world is shifting towards a digital world, surrounded by advanced technology. Thus, implementing big data trends for your business can be and will be definitely a charm. The only thing here is, you need to figure out your purpose of applying them in your business. The sooner you’ll identify – it will become easier for you to pick any trend. So, these are the top 10 big data trends for 2022 that are going to dominate the market one-sided for sure!

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