Big Data: 10 Trends and Technologies

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  Due to the development of e-commerce, data becomes more and more popular with each day. Since the world we are living in changes quickly and unexpectedly. If a business owner wants his company to stay afloat it is essential to keep abreast of the times and be aware of everything that is going on around. If you don’t have enough time to go deep into these complicated issues, just click here and get the job done! However, our team has made up an inventory of 10 most popular modern trends in terms of big data.

  1. Artificial intelligence and small data

  Due to the fact that Covid-19 made people spend more time indoor browsing the Internet, the flows of information became enormous. Consequently, it becomes more challenging to sort out data and separate fake facts from real ones. However, this information isn’t like “big data”, so the term “small data” has emerged.

  Nowadays AI technologies and machine learning have to adapt to these enormous information flows. Moreover, because of it new privacy rules appeared.

  1. Data fabrics

 As data becomes more complex, all businesses require a unified foundation for building and storing information. When data fabric is used as a key architecture, it brings about efficient cohesion of software and hardware. It enables easy external and internal access to a range of sources without data privacy violations. New analytics tools facilitate integration with data lakes, warehouses and hubs.

  1. Data origin issues

 AI and enormous flows of fake facts make people doubt all the data surrounding them. In terms of marketing purposes, even professional analysts find it difficult to assess the reliability of data. Sometimes they are required to use some significant methods and algorithms of information analysis. Consequently, new trends focus on the development of these analytical methods.

  1. Cloud services

  Nowadays cloud computing determines technological progress. However, in recent years people doubted the safety of cloud services, but nowadays even Amazon, Google and Microsoft opt for storing data in such a way. Cloud-based issues become more popular with each year, since they minimize the risk of errors and bugs.

  1. Augmented reality analytics

  Being closely connected to cloud services, augmented analytics is another pivotal trend. Integrated information technologies let specialists conduct some automated data assessment. The Internet of Things provides all Internet users with information of some kind and the ability to process it. This trend fosters universal access to analytics of all possible spheres.

  1. Python language

  As we know, there are a lot of analytics tools. Previously analysts preferred R coding language. Nowadays they more frequently opt for Python instead. It is believed to be more user-friendly. This coding language requires less expertise from analysts. Moreover, unlike R, which is a closed ecosystem. Python enables easy integration with the software.

  1. AI matters

  With each passing year computers perform more and more tasks. AI helps speed up the analysts’ work. Technologies become better at understanding human queries, speech patterns and word relations. AI enables real-time data tracking and analytics. However, for more complicated tasks professional analysts are needed. 

  1. Personalized experience

  Because of Covid-19 pandemic people currently spend more time at home. They work remotely, buy clothes and order food. We trust our devices more than before. 

 Since all information about our Internet activity is being tracked and recorded, professional analysts like those working for DataArt can easily make appropriate decisions for boosting your business. It is entirely beneficial for both business owners and customers as well.

  Information about your personal preferences help offer you some needed products or services via targeted ads and many other appealing things. That is why personalized experience is a new fast growing trend.

  1. Real-time data tracking

  Well, the data flows and is enormous and fast-changing. It is pivotal that analysts can analyze all the information on time. Otherwise, it won’t be valuable anymore. That is why analytical tools for real-time data checking and analysis have become a new big data trend. It makes the process of information collection run faster and more smoothly.

  1.  Analytical graph

  Graph platforms are well-known tools for data explanation and interpretation. It is a kind of a mediator between different departments and users. Graph tools enable people to draw parallels and find something in common between products and the audience without translating this information into a code.