Without data analysis, companies are blind and deaf! This is especially true in today’s world where data analysis allow companies to better understand their market in order to stay ahead of their competitors. Artificial intelligence-based technologies such as machine learning, natural language processing, etc. in combination with data analytics are also becoming increasingly popular among companies. Looks like everyone is talking about these days! So let’s take a look at all these different data analysis styles that could dominate in 2021.
- The wisdom of the decision: – Whatever the company does, there is no doubt that they need to make good decisions if they are to live in a world of competition. Decision Intelligence is basically a combination of Artificial Intelligence and Data Science and decision-making concepts and management science. In simple terms, this means decision-makers such as company heads, shareholders, etc, they can use machine learning skills to gain an understanding of their data and make better decisions using this data. Decision Intelligence is becoming increasingly popular because it provides companies an edge and currently 33% of companies use this technology in all sectors.
- Data News: – Currently, the data analytics field uses multiple data view dashboards to communicate information to decision makers as shareholders in a company. But now data issues are becoming more and more common. Would you like to see facts and statistics about the details listed in the dashboard or see a story that reflects your company’s data journey? Most of you can choose a fun story anytime! And that is why data stories are becoming more and more popular, especially for hackers who have no knowledge of the domain of data analytics. It is also predicted that data stories will become the most popular way to transfer data by 2025. So if you are a good writer and a good data analyst, you are in luck!
- Augmented analytics: – Augmented analytics are becoming increasingly popular with this market predicted to grow to approximately $ 18.4 billion worldwide by 2023. It is therefore not surprising that it is already widely used by 2021 with many growth prospects by 2022. Augmented analytics can improve data analytics already used by companies by discovering new ways to create, develop, and share data statistics with the help of machine learning and artificial intelligence. This means that companies can perform many analytical skills such as creating, analyzing and constructing data models. Augmented analytics also makes it much easier to interact with the data and explain the details of the generated data which helps in data analysis. This has completely changed the face of business intelligence and data analysis where users can easily find data, clean it up, and find mergers or patterns.
- Data Cloud Services: – The data could be huge! Some sources also state that more than 2.5 quintillion bytes of data are generated daily in the world. While large companies like Google can easily manage their data in archives, it is very difficult for small companies to manage and store data in order to obtain data. That’s why cloud services are so popular these days for data analytics. 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 analysis services to companies that use network communications. Therefore, Data as a Help can be used by companies to better understand targeted audiences using data, make some of their own production, make better products according to market demand, etc. In fact, it is estimated that DaaS will be used by about 90% of large companies to make money from data by 2021. DaaS is already supplied by many service providers such as Microsoft Azure, SAP, etc.
- X figures: – Data Analytics is currently limited to one type of data in the form of tables. Especially when anyone is talking about analytics, the data that comes to mind are linear zed numbers in the spreadsheet. However, the company has many other types of data such as video, text, audio, etc. So if companies have to overtake their competitors, they need to use this type of data again. That’s what X analytics means. This could mean video statistics, audio statistics, text statistics, and so on. The most common example of text analytics is emotional analytics where companies can analyze the general feelings and feelings of their customers by reading their reviews. Another example is Google Video Intelligence which helps to analyze and classify content in videos. In fact, X analytics is becoming so popular that 75% of Fortune 500 companies are likely to use it in some way or by 2025.
- Edge Computing: – Data becomes bread and butter for many companies. However, this data is generated in many places, and in particular, cloud data storage devices are far away from where data is generated. It is more expensive to transfer this data and has led to higher data capture. That’s where Edge Computing comes in! Edge Computing ensures that computer and data storage centers are nearing the end of the surface where this data is found or consumed. This is even better than finding these storage facilities in a central location thousands of miles away from the data produced or used. Edge Computing ensures that no data delays can affect application performance and reduce lost data transfer costs. And when you lose money, that technology will definitely be popular.
- Data Blockchain: – Security is becoming more of a problem for companies than ever before. Data is a gold mine of opportunity but this gold mine can also be broken into and companies may lose more than ever before. So the new data security technology is being criticized by Blockchain as one of them. Blockchain is a series of blocks where these “blocks” form digital data connected using cryptography and each block points to the previous block in the chain. Since Blockchain is a distributed technology, it is much safer and more visible. Nowadays many companies use Blockchain from distributed ledgers such as Ethereum, R3 Corda, Hyperledger Fabric, Bitcoin, Quorum, etc. This increases data security and improves data quality because only important data is highly protected.