Tech

Top 12 Big Data Technologies to Adopt in 2021

Big Data Technologies

Big data technology is a term that we are hearing a lot these days. Big data technology is not just a buzzword, rather it’s a technology that is a boon in this competitive world. But what exactly does it mean and why is it important for businesses and professionals alike? We’ll find that out in this post!

All you need to know about Big Data Technology

Since past few years, there has been a huge influx in the data and IT domain. Nowadays, big data technology has become incredibly important for organizations. When it comes to generating tons of data catering to clients’ needs, big data technology serves as an efficient technique that’s surely going to make a strong impact in 2021.

What is Big Data Technology?

As defined by 2MinutesRead.com Big Data Technology is nothing but a software-utility that is specifically designed to analyse, process and extract information from huge chunks of data, which traditional data processing software cannot do even in a million years.

In simpler terms, it is closely related to other technologies like Artificial Intelligence, Machine Learning, Deep Learning, IoT, and many more. These when used together, generate data that allow businesses to make well-informed decisions.

Before heading to the mushrooming big data technologies, let’s split big data into two categories:

1. Operational Big Data Technologies

This deals with the huge amount of data generated daily that include social media, online transactions, or any sort of data that’s being used in the analysis. There are some of the scenarios that outline the Operational Big Data Technologies include online ticket booking for movies, railways, flights, online trading, and purchasing from Amazon, Flipkart, Walmart, and whatnot.

2. Analytical Big Data Technologies

Unlike operational big data technologies, it refers to the advanced adaption of big data technologies that deal with the investigation of complex and large data sets for important business decisions. Some examples covered in this domain are time series analysis, stock marketing, medical-health records, and weather forecasting.

12 Big Data Technologies Trending in 2021

 Here are some of the leading big data technologies that can influence the market and IT industries. Let’s discuss them in detail!

1. Artificial Intelligence

 The technology that deals in designing smart machines that can perform various tasks that typically demand human intelligence is known as Artificial Intelligence.

Companies, these days, have started adopting AI to get rid of monotonous tasks while focusing on other core operations of the business.

There’s no denying the fact that AI is developing very swiftly and considers many approaches like augmented machine learning and deep learning into account to make a remarkable shift in almost every tech industry.

One of the best things about AI is the ability to make fruitful ad future-oriented decisions that can help a business in achieving its objectives.

AI is arguably evolving to provide holistic benefits to different industries. Be it in the treatment of patients or conducting surgeries or detecting the spread of COVID-19, AI can be used immensely.

2. NoSQL Database

Another popular big data technology is NoSQL that incorporates a wide gamut of separate database technologies that can effortlessly design applications that are modern, seamless, and responsive. It showcases a nonrelational database that helps in data collection and retrieval.

This technology usually stores unstructured data and delivers rapid performance and offers flexibility while allowing organizations to deal with different data types at a large scale. Some of the examples include MongoDB, Redis, and Cassandra.

The technology covers the integrity of design and easy horizontal scaling to an array of devices and ease control over opportunities. As it efficiently uses data structures, it can makes computations easier than before.

There are many companies like Twitter, Facebook, ad Google that store terabytes of user data every single day.

3. R Programming

R is the programming language and an open-source project that can be used for statistical computing, visualization, unified developing environments like Eclipse and Visual Studio assistance communication.

And it couldn’t be wrong to say that it is one of the popular languages across the world. It is also being used by many professionals like statisticians and data miners who design statistical software and mainly in data analytics.

4. Data Lakes

Another bid data technology that has been gaining significant traction among businesses is nothing but Data Lakes!

It refers to a consolidated repository to stockpile all data formats in terms of structured and unstructured data, irrespective of its scale.

When it comes to huge data accumulation, data can be saved without making changes to it and executing different kinds of data analytics from dashboard and data visualization to real-time analytics for better business interferences.

Businesses must utilize data lakes to stay ahead of the competition so that new types of analytics can be conducted such as machine learning across huge data files, social media data, and even IoT devices. one of the best things about the technology is that it helps organizations to know and respond to better opportunities to ensure faster growth of their business by enhancing productivity, engaging customers, maintaining devices actively, and making profitable decisions.

5. Presto

It is nothing but a popular open-source and SQL based distributed query Engine that is incredibly helpful in running queries against the data sources of every scale and different size ranges.

When an organization uses this technology, it can easily query data in proprietary data stores, Cassandra, Hive, and relational database storage systems. Developed by the Apache foundation in the year 2013, this java-based query engine is currently being used by some of the top MNCs including Airbnb, Facebook, Checkr, and Repro.

6. Predictive Analytics

This big data technology helps to predict future behavior via prior data. It is a part of big data analytics that uses data mining and statistical modeling, machine learning technologies, and some mathematical models to predict what could be the future.

When an organization effectively uses this big data technology, it uses tools and models of predictive analysis to find out the latest trends and behavior that could impact the future. The science of predictive analytics can predict upcoming events with more than 90% of accuracy.

Let’s take an instance to understand!

When it comes to exploring the relationship among different trending parameters, this big data technology is used to identify the risk delivered by a specific set of possibilities.

7. Apache Spark

This big data technology is equipped with a multitude of built-in features, helpful in machine learning, streaming, SQL, and graph processing support.

For the big data transformation, it is the fastest and commonly used technology. It supports some of the popular major languages of big data that include Java, Python, R, and Scala.

Due to Apache Spark, Hadoop was introduced, concerning the speed of the data processing. The technology helps to minimize the waiting time between interrogating and executing the program. When it comes to storage and processing, it is being used within Hadoop and it is quite better than other older big data technologies.

8. Tableau

This is the powerful software tool that is being used by leading IT firms, including QlikQ, Oracle Hyperion, and Cognos in the domain of business intelligence.

And it couldn’t be wrong to say that data analysis is a fast machine that is possible with the help of Tableau. Developed by the tableau company in 2013, the technology’s still popular and helps companies to manage their business operations without any difficulty.

It is written in different programming languages like Python, C++, Java, and C.

9. Prescriptive Analytics

This big data technology helps companies the techniques they can utilize to achieve their respective business goals. It can notify a company that the borderline of a product is expecting to decrease and even help in investigating various factors as per the changes in the market and predict the most favorable outcomes.

The technology solely focuses on valuable insights over data monitoring. And the best part is that it gives the best solution for increased business profits, better customer satisfaction, and operational efficiency.

10. In-memory Database

The in-memory database (IMDB) is stored in the main memory of the computer (RAM) and controlled by the in-memory database management system.

If you are planning to use the technology, conventional disk-based databases are configured with the attention of the block-adapt machines at which data is written and read. Instead, it feels the necessity of different blocks to be read on the disk when one part of the database refers to another part.

This is a non-issue with an in-memory database where interlinked connections of the databases are monitored using direct indicators. When it comes to achieving minimum time by skipping the needs to access disks, in-memory databases are built

But there are high chances of losing the data upon a process or server failure as all data is collected and controlled in the main memory completely.

11. Blockchain

Blockchain is a popular big data technology that is on the rise as it carries Bitcoin digital currency with a unique feature of secured data. One of the interesting things about the technology is that once it gets written, it never gets deleted or you can’t make modifications.

And that’s the reason; it is a highly secured ecosystem and can be used in a multitude of industries like banking, finance, insurance, healthcare, retailing, etc.

There’s no denying the fact that the technology is still in the development process. Many merchants of various organizations like AWS, IBM, and Microsoft including startups have already started adopting blockchain technology in your business to streamline operations and become future-ready.

12. Hadoop Ecosystem

The Hadoop ecosystem includes a platform that is helpful in resolving the challenges that surround big data. It includes a range of different components and services that deal with ingesting, storing, analysing, and maintaining.

There are different services common in the Hadoop ecosystem that can complement its different components which include MapReduce, HDFS, YARN, and more. One of the best things about the technology is that it includes both Apache Open-Source projects and commercial tools and solutions, helpful in achieving business objectives.

Future of Big Data Technology

  • Cloud solutions will power Big Data Technologies: Since the Internet of Things (IoT) took the industry by storm, data generation has gained significant popularity.  Applications that require IoT will now need a perfect scalable solution that can efficiently manage complex and large sets of data.

And it couldn’t be wrong to say that many organizations have already started realizing the benefits of these big data technologies on cloud.

Some of the other technologies that have started evolving include In-memory database, Hadoop, IoT, Spark, and more. These are expected to be well on rising in the coming years.

  • Real-Time Solutions will expand: Since big data technologies have started becoming a new-normal, organizations now have a thorough idea of how to store data and efficiently process big data.

In the future, the only difference that is going to happen is that how quickly organizations can deliver analytics solutions and make decisions that could be beneficial in the future.

Talk about the coming era, the prime focus is going to be Speed. And there are significant chances that the processing capabilities of Big Data technologies will increase to an unprecedented scale.

  • Self-Service Big Data applications will continue to evolve: There is no denying that Big Data technologies that simplify data cleaning, prepare data, manage large sets of data are expected to increase.

And it has been observed that tools like Big Data like Tableau with Hadoop will significantly minimize the effort of the users.

  • Hadoop will continue to rock: When it comes to technological advancement, Hadoop is likely to come up with a range of features that will certainly make it ready for different businesses.

Once the security projects of Hadoop like Sentry and Rhinogain will gain a robust foothold, its implementation will expand across a multitude of sectors and companies can efficiently utilize these solutions without compromising the security aspect.

Conclusion

So, that’s a wrap-up to the 12 best big data technologies that will make an impact in 2021 and further!

And it couldn’t be wrong to say that the ecosystem of big data is substantially mushrooming and new technologies are coming into the picture very rapidly. Subsequently, IT organizations and tech giants are making the most out of the technologies to perfectly cater to their needs and budget.



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