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Top 7 Data Analytics Trends for 2021
  • Last Updated : 04 Jan, 2021

Without data analytics, companies are blind and deaf! This is absolutely true in today’s world where data analytics allows companies to understand their market better so that they can stay ahead of their competitors. It’s even possible that data analytics infrastructure may increase 5 times by 2024 because of the rapid increase with which companies are adopting this technology. And that’s not all! Other artificial intelligence-based technologies such as machine learning, natural language processing, etc. in conjugation with data analytics are also becoming more popular among companies.  It seems like all everybody’s talking about these days! So let’s see all these different data analytics trends that may dominate in 2021.

Top-7-Data-Analytics-Trends-for-2021

These trends have already become popular in recent years and have become even more important after the impact of COVID-19. Now that the whole world has gone digital in 2020 with more data being produced than ever before, the importance of data analytics in a post-COVID-19 world cannot be understated. So let’s analyze the data analytics trends such as decision intelligence, edge computing, data storytelling, data cloud services, etc. that are so important going into 2021.

1. Decision Intelligence

Whatever a company does, there’s no doubt that they need to make good decisions if they are to survive in the corporate world. Data Science and Machine Learning can contribute to this decision-making so that companies and improve their bottom line. Decision Intelligence is basically a composite field containing Artificial Intelligence and Data Science along with concepts of decision-making and managerial science. In simple words, this means that decision-makers like corporate heads, shareholders, etc. can use machine learning algorithms to obtain insights from their data and make the best decisions by leveraging this data. Decision Intelligence is becoming more and more popular because of the edge it provides companies and currently around 33% of companies use this technology across all sectors. (If it’s a company you’ve heard of, most probably they use Decision intelligence!)

2. Data Stories

Currently, the field of data analytics uses a lot of data visualization dashboards to communicate the data to decision-makers such as shareholders in a company. But now data stories are becoming more and more popular. Would you prefer to just see facts and figures about the data arranged in a dashboard or see a story that shows the data journey for your company? Most of you would pick a good story any day! And that’s why data stories are becoming so popular, especially for laypersons who don’t have domain-specific knowledge of data analytics. Gartner even predicts that data stories will become the most popular method of conveying data insights by 2025. So if you are a good storyteller along with being a good data analyst, you are in luck!



3. Augmented Analytics

Augmented analytics is becoming more and more popular with this market predicted to grow from $8.4 billion in 2018 to around $18.4 billion globally by 2023. So it is no surprise that it is already heavily used in 2020 with more prospects for growth in 2021. Augmented analytics can enhance data analytics already used by companies by finding a new method of creating, developing, and sharing data analytics with the help of machine learning and artificial intelligence. This means that companies can automate many analytics capabilities such as the creation, analysis, and building of data models. Augmented analytics also makes it much easier to interact with the data and explain the data insights generated which help in data exploration and analysis. This has entirely changed the face of business intelligence and data analytics wherein users can easily obtain the data, clean it, and then find correlations or patterns.

4. Data Cloud Services

Data can be huge! Some sources even say that more than 2.5 quintillion bytes of data are created every day in the world (that’s 9 zeroes!) While big companies like Google can easily handle their data in warehouses, it’s very difficult for smaller companies to manage and store data in order to obtain insights. That’s why cloud services are becoming so popular these days for data analytics. Just like Software as a Service, Data as a Service(DaaS) is a cloud service that uses cloud computing to provide data storage, data processing, data integration, and data analytics services to companies using a network connection. Hence, Data as a Service can be used by companies to better understand their target audience using data, automate some of their production, create better products according to market demand, etc. In fact, it is estimated that DaaS will be used by around 90% of large companies in order to generate revenue from data by 2020. DaaS is already provided by many service providers such as Microsoft Azure, SAP, etc.

5. X analytics

Data Analytics till now is mostly limited to a single type of data that is in tabular form. Mostly when anyone talks of analytics, the data that comes to mind is rows upon rows of numbers in a spreadsheet. However, a company also has many other forms of data such as video, text, audio, etc. So if companies have to move ahead of their competitors, they need to utilize this type of data as well. That’s what X analytics is all about. This can mean video analytics, audio analytics, textual analytics, and so on. A very common example in textual analytics is sentiment analytics wherein companies can analyze the general mood and sentiments of their customers by studying their reviews. Another example is Google video intelligence that is useful in analyzing and classifying objects in videos. In fact, X analytics is becoming so popular that 75% of Fortune 500 companies might be using it in some shape or form by 2025.

6. Edge Computing

Data is becoming the bread and butter for most companies. However, this data is generated in many places, and mostly, the physical data storage devices for the cloud are far away from where the data is generated. It becomes very costly to transfer this data and also leads to higher data latency. That’s where Edge Computing comes in! Edge Computing makes sure that the computational and data storage centers are closer to the edge of the topology where this data is generated or where it is consumed. This is a better alternative than having these storage centers in a central geographical location which is actually thousands of miles from the data being produced or used. Edge Computing ensures that there is no latency in the data that can affect an application’s performance and also reduces the money lost in data transmission. And where there reduction in the loss of money, that technology is sure to get popular. Gartner predicts that 75% of all the data that is managed by companies will be processed using edge computing as compared to only 10% in 2018.

7. Blockchain for Data

Security is becoming a much bigger issue for companies than ever before. Data is a goldmine of opportunities but this goldmine can also be hacked and companies could suffer higher losses than they ever have before. So new technologies for data security are becoming critical with Blockchain as one among them. Blockchain is a chain of blocks where these “blocks” constitute digital information that is connected using cryptography and each block references the previous block in the chain. Since the Blockchain is a distributed technology, it is very secure and also transparent. These days many companies are using Blockchain from the available distributed ledgers like Ethereum, R3 Corda, Hyperledger Fabric, Bitcoin, Quorum, etc. which increase the data security and in turn improve data quality because only the important data is protected so much.

Conclusion

2021 is a new year with new hopes and beginnings (and hopefully no CORONA!) All these data analytics trends may change the working of companies in 2021 and provide an advantage against their competitors. Some big names are already using these technologies to great effect. For example, Coca-Cola uses X analytics of all the Email, social network, and phone feedback they get from their customer to devise their company strategy. Data Stories is an AI company that provides augmented analytics so that its customers can predict and improve their business KPIs. Microsoft is a key player in edge computing that provides edge services to other companies and so on.

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