Best Tools and Technologies for Big Data Analytics

Big data continues to dominate different parts of the business industry. On the other side, the amount of data contributed by different organizations across the industries continue to increase in volume. However, approximately 95% of organizations still struggle with managing and using unstructured data format in their daily operations. It's no secret that the data generated from the organization's activities incorporate a lot of insights that can be used to predict the company's future and applied in decision-making. 

Besides, the business executives who need to get the best out of the data they generate consider looking at real-time data analytics capabilities to ensure they can get the best out of the data they generate. This is only possible if organizations can heavily invest in data analytics tools and technologies that will play a huge role in ensuring that the data generated has been analyzed to generate insights. 

There are multiple technologies for big data analytics that you can choose from and use to mitigate all your data analytics needs. However, it's a good idea to have some first-hand information about every option available on the market to help you solve your data visualization needs. Note that big data analytics is a comprehensive sector that needs a lot of attention and investment to ensure your business is running in the right direction. 

This article discusses some of the best technologies for big data analytics available on the market that can serve your data needs better. 

Delta Lake 

Delta Lake is a big data analytics tool invented by Databricks Inc, which was also established by the creators of the spark processing engine. According to the inventors of the software, it is an open format storage layer mainly focused on delivering reliability, security, and performance on your data. It can be utilized for both lake streaming and data batch operations. Note that this software does not replace the data lakes. 

Instead, it's designed to stay at the top of the lakes, creating a single home for the semi-structured, structured, and unstructured data. As a result, it eliminates the cases of data silos. Delta Lake can also help you mitigate corruption cases since it offers fresh data, faster processing of data, and supports compliance efforts within an organization. 

This big data analytics tool has the power to support ACID transactions; it comes with a set of spark-compatible APIs and stores data in an open apache, making it easily accessible to its respective users. 

Druid 

If you are looking for a real-time analytical reporting tool, Druid is the real deal! The software has much lower latency, especially for queries, and a much higher concurrency. Also, it comes with much higher multi-tenant capabilities and total visibility in data streaming. The tool gives access to multiple end users who have the freedom to query the data that is stored within the software. 

The tool is mainly written using the Java Programming language. Druid was invented in 2011 and later changed to Apache technology in 2018. This is the best alternative compared to any traditional data warehouse that works well when analyzing event-driven data. Similar to a data warehouse, Druid mainly uses the column-oriented storage mechanism, which is also used to load files using batch mode. 

The tool comes with flexible schemas and a native support system tailored for the nested and semistructured data. Also, it has a native inverted search index that speeds up searches and saves time. 

Hive

This big data analytics tool is considered an SQL data warehouse infrastructure used for reading, writing, and managing large data sets. The software was initially invented by Facebook and later acquired by Apache. Currently, the software is under the management of Apache, which is in charge of all its development and management activities. Hive is one of the best tools that you can use to process structured data. 

In most cases, Hive is used in data summarization, querying a massive amount of data, and data analysis. However, the tool cannot be used to facilitate online transactions and generate real-time updates. The developers of Hive consider it a highly scalable, flexible, and fast tool that you can use in your data processing needs. It comes with a standard SQL functionality used for data querying and analytics. 

Kafka

Kafka is among the best event streaming platforms that many organizations across the globe use. The tool supports the operation of data pipelines, data integration, and streaming analytics to ensure that companies get real-time information from their respective data sources. This is also considered an analytical reporting tool mainly used to store, read, and analyze streaming data within a company environment. 

The data combines the application of data streams and systems to make it applied in different scenarios within the organization. The software was instigated by LinkedIn in 2011 and later handed to Apache, which has taken over the management of the tool across different platforms. Kafka has five core APIs used for Java and the Scala programming language, which are used in data processing. 

Storm 

This is another open-source technology managed by Apache. It is propelled by real-time data computation specifically designed to process any form of unbound streams of data. According to the tool's developers, it can be used in managing real-time analytics and online machine learning activities to facilitate the smooth running of data processing operations across the organization. 

The Storm data processing operations continue to run full-time to ensure that the respective organization gets access to process data that can be used in decision-making. Besides, the system is created in a false tolerant manner to ensure that all your data needs are processed, and you can access a better data format that enhances business operations. 

The tool utilizes the Apache zookeeper technology that enhances the coordination of clusters. A storm is a user-friendly tool you can easily utilize to mitigate your data visualization needs within your organization. 

Airflow

Airflow is a popular workflow management system used for scheduling and running complicated data pipelines that are closely associated with big data systems. This system is meant to ensure that all the tasks within the organization are executed depending on the required schedule and order. This tool is integrated into the company system to enable it to get access to the essential company information associated with the management of the company activities. 

The tool is extremely easy to use since the workflows are created using the python programming language. Also, it can be utilized in establishing machine learning models, which play a key role in transferring data from one point to another. This technology began as an Airbnb in 2014 and was later announced as an open source technology in 2015. 

Final Verdict

Gathering insights from big data is a difficult task and many people across the globe struggle to get the job done. According to researchers, approximately 63% of organizations cannot generate insights from the big data they generate from their daily operations. However, acquiring the right big data analytics tool can help business owners find a lasting solution to this problem and enhance the success of their business operations. The big data tools and technologies outlined in this article can help organizations elevate their game in business.