Best Big Data Analytics Software in 2024 — Which to Choose
Discover the best big data analytics software in 2024 and find the perfect solution for your business needs and objectives.
Nowadays, collecting big data in the market has become an important part of maintaining business consistency.
With growing customer expectations, business competition, and economic uncertainty, leaders must extract maximum value from their data. So how can businesses exploit the full potential of their data?
To steer your business in the right direction, you need the best tools to analyze big data based on your business goals and needs. Let’s explore some of the best big data analytics software in 2024.
I. What is Big Data Analytics
Big data analytics refers to the complex process of using methods, tools, and applications to collect, process, and extract data from large, diverse, and fast data sets. This big data can come from many different sources, such as websites, mobile devices, email, social networks, and networked smart devices. They vary in form, from structured (database tables, Excel sheets) to semi-structured data (XML files, websites) and unstructured data (images, audio files).
Big data has become a buzzword since the early 2000s when software and hardware made it possible for organizations to process large volumes of structured and unstructured data. With the explosion of big data, early innovative projects were developed to store and process these vast datasets. Today, big data analytics methods are used alongside emerging technologies such as machine learning to discover and scale more difficult and complex insights.
II. Why Big Data Analytics Technologies are Necessary to Businesses
Now you know what big data analytics is. But why is it important? Why are big data analytics technologies necessary for businesses?
1. Cost savings
The rise of smartphones, social media, smart technology, and machine learning allows us to transfer large amounts of data at breakneck speeds. Thanks to big data analytics, businesses can use that information to answer important questions. It allows organizations to use vast data from various sources. This helps identify opportunities and risks for businesses to grow and improve their profits quickly.
2. Product development
Big data analytics software enables businesses and organizations to adopt a more comprehensive, data-driven approach to decision-making, fostering future growth and innovation. For instance, Spotify leverages big data analytics to understand its users’ listening habits and preferences. By analyzing data on when, where, and what users are listening to, Spotify can create personalized playlists, recommend new songs and artists, and develop features that enhance the user experience. So, leveraging big data analytics software helps Spotify continuously innovate and improve its services, resulting in higher user satisfaction and retention.
3. Market insights
Big data analytics software allows tracking purchasing behavior and market trends. It helps companies collect and analyze customer data from various sources such as customer feedback, shopping history, and social media interactions. Through this analysis, companies can more accurately grasp what can solve bottlenecks in the supply chain. Additionally, healthcare providers can explore new options for clinical care based on patient data trends.
III. Top 10 Big Data Analytics Software 2024
Big data analytics tools and technologies play an important role in businesses. In this section, we will examine the top 10 most popular big data analytics tools and technology in 2024.
1. Zoho Analytics
Zoho Analytics is a big data analytics software that offers visual analytics and dashboards. It is used by famous brands such as Hyundai, Ikea, HP, and Philips. This software enables you to integrate various data sources, such as business applications, databases, cloud drives, etc. Its freemium plan allows you to add up to 2 users, import up to 10K rows/records, and access unlimited reports and dashboards. It is pretty good software for free data analysis. Zoho Analytics includes a library of pre-built visualizations categorized by functions like social media, finance, IT, and sales, making it easy to use.
2. Tableau
Tableau is an intuitive big data analytics software that is easy to use and user-friendly with built-in best practices for data exploration.
Tableau offers a drag-and-drop interface, making it easy for users to utilize analytics tools and interactive dashboards with little learning required. Therefore, with a simple and easy-to-use interface, users can easily use this tool regardless of their technical abilities. Tableau includes numerous features and tools for creating visualizations quickly. These visualizations provide context to raw data and make it easy to comprehend.
Tableau stands out with its exceptional visuals and interactive elements. However, it is limited to data visualization and does not support pre-processing. Additionally, its high cost and steep learning curve can be challenging for learners.
3. APACHE Hadoop
Big data analysis software is being processed and stored using this Java open-source platform and the data can be processed efficiently and in parallel thanks to the cluster system. Data from a server can be processed by multiple structured and unstructured computers, and Hadoop users can also access that data across various platforms. Today, tech giants like Amazon, Microsoft, and IBM use it as one of the premier tools for big data analysis.
4. Atlas. ti
Atlas.ti is an all-in-one big data analysis software. This big data analytics tool gives you all-in-one access to the entire platform range. You can use it for data analysis and mixed methods research in academic, market, and user experience research.
Atlas.ti is powerful qualitative data analysis software. It offers many features to support your research. It helps you organize, encode, analyze data, and create visualizations and reports.
5. Apache Spark
This is one of the most powerful open-source big data analytics software. It offers over 80 high-level operators to help businesses easily build parallel applications. Furthermore, with its user-friendly APIs and capacity to process multiple petabytes of data, Spark is employed by many organizations to manage large datasets, perform multi-tasks, and execute at scale. “Due to its significant relevance for ML and AI, many leading tech companies are now turning to Spark.
6. SAS
SAS is considered one of the best big data analysis software used today to create statistical models. Data scientists can easily manage data from various sources and mine, extract, or update data using those data. With Statistical Analysis Systems (SAS), data can be accessed in SAS tables or Excel spreadsheets. Additionally, SAS has also introduced new tools used in big data to understand artificial intelligence and machine learning.
7. Power BI
Power BI is a big data analytics software from Microsoft, known and loved for groundbreaking features like Natural Language queries, Power Query editor support, and intuitive User Interface. It also offers advanced Interactive Visualization and Business Intelligence capabilities. Because it is a Microsoft product, you can enjoy seamless integration with many different Microsoft products. Furthermore, it can let you connect to Excel spreadsheets, cloud data sources, and on-premises data sources.
However, Power BI has some limitations, including its inability to manage records larger than 250 MB. Additionally, you may have to pay extra to scale according to demand since it has limited sharing capabilities.
8. Qlik Sense
This is the great big data analytics software for purchasing departments. It is a comprehensive data analytics software with an innovative associative analytics engine. Users can explore data from any angle. They are not limited by pre-aggregated data or predefined queries. This flexibility is ideal for purchasing departments. It provides in-depth supplier and industry trend comparisons. In addition, it offers convenient currency filters for international transactions. Detailed reports on low product availability or expenditure are also available.
9. Rapid Miner
Rapid Miner is a stand-out big data analytics software designed to automate the creation of data analytics workflows using visual tools, eliminating the need for coding. It is widely used in sectors like education, training, and research. Despite being open-source, RapidMiner has limitations, such as supporting only 10,000 data rows and one logical processor. It enables the deployment of machine learning models to web or mobile platforms, provided the user interface is ready for real-time data collection.
10. Splunk Enterprise
This is trusted big data analytics software for leading companies. Splunk Enterprise is utilized by 91 of the Fortune 100 companies, including Intel, Comcast, and Coca-Cola. It provides machine learning-focused insights, featuring capabilities, such as entity profiling and scoring, risk behavior detection, anomaly observation, and high-fidelity behavior-based alerts. Users can try a free cloud-based sandbox trial of Splunk UBA before deciding. Splunk offers specialized solutions for DevOps, Security, IT, and big data, making it a versatile tool for various industries.
IV. Final Thoughts — Which is the Best for Your Business?
Every big data analytics software provides distinct features and benefits that address various business needs. Therefore, choosing the best big data analytics software for your business depends on your specific needs and goals, as well as your operational requirements, scalability, and budget constraints.
Evaluate each option against key criteria to make informed decisions that will advance your data analytics and drive your business forward in 2024.
