
Data Management
Top Trends 2022 - Data Analytics
By TechDogs Editorial Team

Overview
If only we all could get something like Dash (from Minority Report, duh!) who could model, inspect, transform and even predict using data to make decision-making easier. With the combined minds of Dash, Agatha and Arthur (the three Precogs or pre-cognitive beings), they were able to stop a crime even before it happened. Imagine what they could manage for your company had they been a resource you could tap into!
Knock! Knock! Reality check - that was fiction and not even close to what's happening in the world of Data Analytics at the moment. While you can't get your hands on those fictional Precogs, you can definitely tap into some of the up-and-coming trends to analyze your data right.
Read on to explore the most definitive and revolutionary Data Analytics trends that are shaping the way people handle and leverage the power of data in 2022!
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Here's a fact for you - Netflix invested over $100 million to get the rights for the US version of "House of Cards." What made them invest in a remake which already had a British version that was famous enough?
Before you say, "it had such an interesting plot" or "it was directed by David Fincher," hold on. #ThisIsNotAFairyTale
There's another fact you should know - this was the first time Netflix had invested such a big amount of money on content.
Clearly, they had to base their decision on more factors than just the plot and director, right? They considered you - the audience and the data they had from your viewing patterns. We're not just talking about what you watched or scrolled through, they tracked when you watched, when you paused, where you watched from, which device you used, your searches (all 3 million of them!), your ratings (4 million of them!) and a lot more. They took all that data and analyzed it before giving a green signal to the investment.
Much like Netflix, every business wants to base their decisions on using data science and data analytics in some capacity or the other. In fact, most soccer clubs use data analytics to improve players' performance, squad formations, tactics and fitness regimes. The main aim is to enhance the accuracy of their business intelligence-based decisions and make them as foolproof as possible. These two key goals (soccer pun intended!) have been, are and will always be driving Data Analytics and the technologies related to it.
The question is - what's next? How are businesses getting closer to analyzing more and analyzing better? Well, we've got the answer. Check out these top 5 Data Analytics Trends that will shape the data-crunching game in 2022!
Trend 1: Analytics Will Happen In Multi-cloud Environments

Do you realize how a lot of the data on your smartphone is stored on Google Drive or iCloud? It is where your data is stored safely for you to access it from everywhere and any device. Similarly, for the last few years, companies have been using cloud environments to store bulk data along with its backup. As the data generated is increasing, the need for multi-cloud is on the rise too, especially because of the easy risk management, speedy performance and reasonable prices.
Multi-cloud gives predictive and Data Analytics new wings because it's cheaper, scalable and yet more secure than public clouds. This makes businesses focus more on the actual analytics of data and less on "let's get this data from here and that one from there." Thus, around 81% of enterprises have reported having a multi-cloud strategy already in the works for 2022.
IT leaders truly understand the value of data in the cloud and since data extraction is a big challenge in the industry, multi-cloud will make things easier. That's why companies are keeping their data sets on multi-cloud infrastructures and adjusting their cloud deployment strategies as per their needs. For instance, Google cloud offers BigQuery Omni as their multi-cloud analytics solution. BigQuery Omni users can then connect to their business data without any data movement or copy-pasting - no matter if it's stored on AWS, Azure, or Google Cloud. This trend will signal a shift towards cloud storage and cloud computing in 2022.
TechDog's Opinion: No doubt multi-cloud strategies will be a great solution to securely store different sets of data from different sources but there will be a bigger issue in that sense. For instance, the cost would be much higher when businesses go through the cloud-to-cloud movement of data or "cloud migration." However, we believe that the benefits of having a multi-cloud approach to Data Analytics outweigh its expenses.
Businesses will achieve a high level of agility by matching each part of their business to a specific cloud setup, making operations more seamless. Furthermore, because businesses are currently limited in their ability to optimize multi-cloud operations independently, they will be able to deliver the necessary automate and orchestrate analytics better through multi-cloud infrastructures by leveraging competent multi-cloud service providers. They will also be able to achieve complete agility and workload mobility between heterogeneous cloud platforms, cloud storage and virtual machines with the right multi-cloud infrastructure.
Trend 2: We Will See The Rise Of Augmented Consumers

We are all used to working with the dashboards that go with the pre-defined data exploration approaches, right? However, the data management and analytics dashboards we are currently using are somehow restricted to limited POVs (point of views). Now, the time has changed and analytics will be more futuristic. How about something that is more customer-focused, powerful, friendly and relatable? That's what Data Analytics in 2022 would have.
Having advanced ways for data analysis will be very handy for businesses because the main focus will be to develop and deploy an advanced system that is more supportive of augmented analytics. One such advancement is the augmented consumer approach – it refers to business users who rely on powerful automated, contextual and mobile capabilities as part of their analytics workflow. The augmented consumer differs from typical analytics users in that they do not rely on traditional dashboards as their primary means of analyzing data. Instead, when exploring business data, they will rely on the easier access to sophisticated augmented features such as automated alerting and natural language query (NLQ).
Take it from research firm Gartner, which says, "organizations need to widen the focus of their advanced analytics capabilities and initiatives, enabling data analysts to (become) augmenting consumers. Data Analytics leaders must view this shift as pivotal in getting more people to use data in more decisions." Augmented customer approach will soon replace conventional dashboards with better, more responsive Data Analytics capabilities while being more accessible to business stakeholders.
TechDog's Opinion: We predict that the augmented consumer dashboards will bring out various possibilities for businesses that were earlier offered only to niche data scientists and data professionals. From 2022, thanks to augmented consumer approaches, all the insights will be available to anyone in the company and not just restricted to the experts or decision-makers. Moreover, the augmented consumer dashboard's features will generate insights dynamically and automatically according to the changing business needs.
We believe that the true value of an augmented consumer strategy lies in the fact that it will reduce the reliance on manual exploration of data - a step that always precedes Data Analytics. This will allow business analysts to go beyond surface-level predictive analytics and get more granular insights – and that too much faster.
Trend 3: Smarter Artificial Intelligence To Analyze Data

Sometimes it is quite challenging for the companies to get the right technology to scale their Data Analytics pipeline, as the data they have been collecting increases. Enter Artificial Intelligence (AI) – which gives more responsive, highly intelligent and pretty scalable solutions to the business landscape. Sure, they have been around for a while now but this time, the need for AI will be on the rise.
Currently, 48% of large enterprises use Machine Learning and Artificial Intelligence tools to address their data quality issues. However, in 2022, these tools will expand to cover the entire Data Analytics operations. Soon, Artificial Intelligence will automate and optimize Data Analytics for businesses, discovering insights quicker, finding new patterns and relationships in the data through powerful algorithms. Yeah, even a room full of us humans are no match for these new-age technologies!
How do you think Netflix suggests what to watch next to millions of users after they are done watching a recent series? It's not based on the top views or analysis done by data analysts but more by identifying each viewer's preference. Even though it is pretty challenging for the entertainment company to get that right, it did manage to get itself a winning solution – an AI-based recommendation system! Needless to say, having an AI system will allow businesses to deal with real-time Data Analytics and make better decisions in the future.
TechDog's Opinion: When we talk about AI, it always seems like it works with the historical data to analyze trends and predict business insights based on it. However, the future is different because Artificial Intelligence wouldn't need historical context anymore, especially once it partners with flexible Machine Learning and small data techniques. This will allow businesses to analyze on the fly – no matter how large or unique the data is.
Moreover, we believe, that using AI within Data Analytics is inevitable - primarily because it will enable businesses to analyze 24x7 without interruption or breaks. In 2022, excellent AI-based Data Analytics systems will make things simpler for analysts through automation, zero downtime and faster learning rates. These systems will even be able to look at previously unseen data and churn out relevant forecasts based on its understanding of the data.
Trend 4: Data Catalog And Data Discovery Tools Will Increase

Investing in the best technologies and tools used to feel like a great advantage to lead in the market race - but they don't anymore. Having a smart analytics tool is not enough to help companies stand out. The Data Analytics workflow will be stronger only when they keep track of how their business data transfers from one place to another. This is the reason why many companies will now invest more in data catalog and discovery tools to get that rising feel again.
According to surveys, more than half of the large businesses are using data discovery and catalog tools to make things flow easily within the company. A State of Data Engineering survey by Immute shows how 60% of 372 companies are using such tools while only a few companies don't follow such advancement. In fact, according to the Data Mesh model of Zhamak Dehgani and Thoughtwork, 'Data discovery is a new approach rooted in the distributed domain-oriented architecture.'
This shows that businesses will begin adopting more data catalog and discovery tools to keep track of how data is moving and changing in their ecosystem to quickly discover, understand and manage all their data assets. This is as critical as the actual analytics, as poorly cataloged data will result in poor quality of analysis or incorrect insights. Hence, in 2022, we will see more businesses augmenting their Data Analytics approaches with robust catalog and discovery tools.
TechDog's Opinion: As data catalog and discovery tools are coming to a boom, even companies who do not even consider themselves data-relevant will put these tools on priority. The major credit goes to these tools’ ability to improve data governance and to make the data more accessible, visible and compliant for every user. That's the major change businesses will see in 2022 making this one of the top data trends this year.
Also, as technology becomes more advanced day by day, there will be innovation and better data-driven approaches will be put into action. However, businesses will first need to ensure their data is up-to-date and meets the quality standard before analyzing it. This data analytics trend will surely ensure the overall development of the organization’s Data Analytics strategy – without a data catalog and discovery tool it will be much harder to implement and maintain in the long run.
Trend 5: Data Management Will Be Critical For Data Fabric Approaches

'What do you mean by data fabric?' you may ask. Well, to be precise, data fabric is an architecture that makes excellent data visibility possible and also allows you to copy, transfer and access data on hybrid cloud storage. When data fabric will come into play, businesses will be able to analyze everything in real-time because the business, the data owner, will be in complete control.
Data fabric is an awesome trend that will make data easy to handle and help you easily figure out what is where and what should not be there. What would it be like if you moved an important file that is not in use anymore but may still need to be accessible to others? Through a data fabric, you can choose to make specific data accessible across a choice of endpoints, spanning hybrid multi-cloud environments. Quite manageable through a data fabric approach – cool, right? Take it from Primary Data CEO Lance Smith who says, "We send it out to any object store that anyone wants... If someone pushes their entire infrastructure into the cloud, we are still applicable in that scenario."
However, it goes beyond simple data – even applications, compute and data resources can be made available through a data fabric. As you might have guessed, this allows seamless, real-time integration and access across multiple data silos to all users. Moreover, the business is in complete control the entire time, reducing security lapses and data theft.
TechDog's Opinion: Data fabric is a brilliant architecture that data managers can soon use to get access to data from its storage in real-time – from anywhere and using any device. Moreover, they could have more storage-centric management for better privacy and governance. This will allow businesses to customize views for each employee by implementing dynamic governance policies. For example, it would be a benefit for the medical industry as hospitals could use the data fabric approach to store the medical images into segments, instead of keeping everything under the same access.
This would make managing the medical data easier and even help keep the entire data away from malware and cyber-attacks. We believe, the data fabric approach will provide a unified data environment, with better scalability, lower costs and improved accessibility while still being robust to external data hacks. This will certainly influence the conventional data science and data management strategies, as data analysts would have access to processed data and analytics in real-time.
Conclusion

You know how important it is to do Data Analytics accurately, it's not just a fashion anymore but more of a necessity. One takeaway from these trends is that data-keeping would no longer require gigantic piles of Excel sheets but a cloud-based system that you can access more conveniently. Hence, businesses need to create a more data-liberal workforce and that is possible only if you follow the latest trends in the Data Analytics market – from adopting data fabric approaches and AI-based tools to investing in data catalog and discovery capabilities and implementing augmented customer strategies – improving the data literacy of the workforce.
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