Marketing Analytics Blog | Adverity

7 Essential Big Data Analytics Tools Every Business Needs in 2024

Written by Irina Prevalova | Nov 21, 2024 2:18:16 PM

Data floods in by the second, fueling every facet of business operations. Yet, raw data offers little value on its own — this is where big data analytics tools step in, transforming numbers into actionable insights.

These tools can analyze large datasets and gather actionable insights from raw data. The insights, in turn, can help in strategic decision-making, improve customer experiences, and streamline workflows.

As they come, big data analytics tools are an indispensable part of modern business strategies. But with so many tools available, how do you choose the right one? 

In this guide, we will introduce you to big data analytics and will tell you about some of the most essential big data analytics tools for 2024, breaking down their key features, benefits, and what makes them stand out in a crowded market.

What Is Big Data Analytics and How Does It Work? 

Big data analytics is about examining large and varied data sets - often called big data - to uncover hidden patterns, correlations, market trends, and customer preferences. This information can then be used to make more informed business decisions. 

There are 3 main big data categories - structured, semi-structured, and unstructured. Making sense of the different types of data is what these tools do best. After all, data-driven marketing is more reliable and predictable.

The process of big data analytics typically involves 5 steps:

  1. Collecting data from different sources
  2. Storing the data in warehouses or in the cloud
  3. Processing the data, including cleaning, organizing, and transforming it into a suitable format
  4. Analyzing the data to find patterns, trends, and insights
  5. Visualizing the data through charts or graphs to make it easy to understand

These are the steps that big data analytics software helps you complete quicker and better. But why should it matter for marketers?

The Importance of Big Data Analytics for Marketers and Businesses

For marketers and businesses, big data analytics is a game-changer as it can help them improve their marketing strategies. It allows them to understand customer behavior on a deeper level, predict future trends, and personalize marketing efforts. 

With the right analytics tools, businesses can optimize their campaigns, improve customer satisfaction, and ultimately increase their bottom line. On top of all that, big data analytics tools can automate many processes, helping you save time and energy that you can spend elsewhere.

Key Factors to Consider When Selecting Big Data Analytics Tools 

With hundreds of different tools for big data analysis out there, how can you choose the right one for your needs?

To maximize your usage and benefits of the tool, you need to choose wisely. That’s why you should consider the following seven factors when sifting through your options. 

Handling large volumes of data 

How big is big data? The big data analytics tools you shortlist must be capable of processing and analyzing large volumes of data efficiently. Look for tools that offer high-performance computing and can scale with your business as your data volume grows.

Scalability & performance 

Scalability is truly essential for businesses that anticipate growth. A good analytics tool should be able to scale seamlessly, handling increased data loads without sacrificing performance.

Ease of use & features 

A user-friendly interface and intuitive features are super important for ensuring that your team can effectively use the tool. Only consider tools for big data analysis that offer customizable dashboards, drag-and-drop interfaces, and easy-to-understand reporting features. That’s how you can make sure to get your money’s worth.

Integration & compatibility 

Your big data analytics tool should integrate seamlessly with your existing systems and tools, such as CRM platforms, marketing automation software, and data storage solutions.

Compatibility is key to creating a unified data ecosystem that allows for smooth data flow across platforms.

Cost-effectiveness

Balancing features with budget considerations in big data analytics tools is crucial.

Evaluate the pricing models of different tools to make sure you’re getting the best possible deal for your investment. Some tools offer flexible pricing plans that allow you to scale usage and features as needed.

Data sources 

To create a centralized point of data collection and analysis, you need to make sure that your chosen tool has the right data connectors for automated data integration. From social platforms and GA4 to Shopify and more, keep an eye out for sources you deal with.

Security & compliance

With data breaches becoming increasingly common, making sure that the large data analysis tools you consider provide robust security features is critical. 

Look for tools that offer encryption, access controls, and compliance with industry regulations to protect your data.

 

 

7 Best Big Data Analytics Tools to Consider in 2024 

Now that we’ve covered the basics of big data analytics tools and how to choose between them, let’s get started on our list of the best tools. We’ll tell you about their features, pricing, and what they’re best for. So, let’s get right to it.

1. Adverity - best for comprehensive marketing data integration and advanced data quality features


Overview 

Adverity is one of the leading big data analytics solutions designed specifically for marketers and data analysts as it offers powerful data integration, analytics, and visualization tools that help businesses make data-driven decisions quickly and effectively. 

With Adverity, you can automate data collection from multiple sources, streamline data processing, and gain actionable insights through customizable dashboards. Through Adverity, you can send the cleaned and transformed data to any data visualization tool of your choice for further analysis and decision-making.

Key Features 

  • Automated data integration from 650+ of data sources
  • Automated data documentation
  • AI-powered copilot for better data transformation
  • Advanced data quality monitoring features
  • Exceptional scalability features

Review 

G2: 4.5/5

Pricing 

Pricing for Adverity’s platform is custom, based on your project’s specifications. If you’d like to get to know the product more before making an investment, you can get a free demo.

 

2. Zoho - best for SMBs 

Overview 

Zoho Analytics is a self-service business intelligence and big data analytics platform that offers a wide range of data visualization and reporting tools. It’s ideal for small to medium-sized businesses looking for an affordable and easy-to-use analytics solution.

Key Features 

  • Drag-and-drop interface for creating reports and dashboards
  • Integration with over 500 data sources
  • AI-powered data insights and predictive analytics
  • Collaboration features for team-based data analysis

Review 

G2: 4.3/5

Pricing 

Zoho Analytics offers a business intelligence platform for both cloud and on-premises data transfers. For its cloud solutions, it offers:

  • 15-day free trial
  • Basic plan for 2 users and 0.5 million data rows ($30/month)
  • Standard plan for 5 users and 1 million data rows ($60/month)
  • Premium plan for 15 users and 5 million data rows ($145/month)
  • Enterprise plan for 50 users and 50 million data rows ($575/month)

 

3. Tableau - best for data visualization


Overview 

Tableau is another one of the leading data visualization and big data analytics tools that helps businesses transform raw data into interactive, easy-to-understand visualizations. 

It’s widely used by organizations of all sizes to create compelling dashboards and reports that drive business decisions.

Check out Adverity's Tableau connector here.

Key Features

  • Wide range of data visualization options
  • Real-time data analysis and collaboration features
  • Integration with various data sources, including Excel, SQL, and cloud services
  • Strong community support and extensive learning resources

Review

G2: 4.4/5

Pricing 

  • Tableau viewer plan to view and interact with dashboards ($15/user/month)
  • Tableau explorer plan to complete full-service analysis ($42/user/month)
  • Tableau creator plan to access end-to-end analytics workflows ($75/user/month)

 

4. Supermetrics - best for entry-level marketing data aggregation 


Overview 

Supermetrics is one of the simplest big data reporting tools. It automates data collection from various marketing platforms and consolidates it into a single dashboard, making it easier to track campaign performance and analyze marketing ROI.

One of the biggest differences between Adverity and Supermetrics is their scale of services. Supermetrics is for entry-level data transfers of raw data into limited destinations. Adverity, on the other hand, is a full-scale data platform.

Key Features 

  • Integration with over 140 marketing platforms
  • Automated data collection and reporting
  • Customizable dashboards for tracking key metrics
  • Google Sheets and Excel add-ons for easy data manipulation

Review 

G2: 4.4/5

Pricing 

  • Essential plan with 1 data destination (such as Google Sheets) and 3 sources - from €29/month (billed annually)
  • Core plan with 1 data destination and 27 sources - from €159/month (billed annually)
  • Enterprise plan with 1 or more data destinations and 128 sources - from €899/month (billed annually)


5. Apache Spark - best for big data processing 


Overview 

Apache Spark is another one of the most popular big data analytics tools out there. It is an open-source big data processing engine that supports complex analytics, including machine learning and graph processing. 

It’s designed to handle large-scale data processing tasks quickly and efficiently, making it ideal for businesses with substantial data needs.

Key Features 

  • Real-time data processing and analytics
  • Supports multiple programming languages, including Java, Scala, and Python
  • Advanced machine learning and graph processing capabilities
  • Scalable and fault-tolerant architecture

Review

Capterra: 4.5/5

Pricing 

Apache Spark is 100% open source and free for public use.

 

6. Power BI - best for business intelligence


Overview 

Power BI, developed by Microsoft, is a business analytics tool that provides interactive visualizations and business intelligence capabilities. It’s a popular choice for connecting multiple data sources, analyzing big data, and generating detailed reports.

Check out Adverity's Tableau connector here.

Key Features 

  • Integration with a wide range of Microsoft products and other data sources
  • Real-time analytics and interactive dashboards
  • AI-powered insights and natural language queries
  • Collaboration tools for sharing reports and insights across teams

Review 

G2: 4.5/5

Pricing 

  • Free version available with interactive reports and visual analytics
  • Power BI Pro – see reports shared with you and publish your own ($10/user/month)
  • Power BI Premium Per User - licensing specific users with enterprise-scale features ($20/user/month)
  • Power BI in Microsoft Fabric – sharing reports with anyone (custom pricing) 


7. Improvado.io - best for marketing data integration at a small scale


Overview 

Improvado.io is the last one of the big data analytics tools on our list. It is a marketing data aggregation platform that centralizes data from various marketing and advertising platforms into one place. 

It’s designed to help marketing teams automate their reporting processes and gain deeper insights into their campaigns.

Key Features

  • Integration with over 500 marketing platforms
  • Customizable dashboards and reports
  • Real-time data syncing and updates
  • Advanced filtering and data transformation capabilities

Review 

G2: 4.5/5

Pricing 

Improvado offers custom pricing on all its 3 plans.

 

FAQs 

What are the benefits of effective big data analysis? 

The benefits of effective big data analysis are too many to count, but gaining clarity about your target audience, discovering the best promotional channels, and personalization are worth highlighting. On top of that, big data analysis helps businesses identify inefficiencies, reduce costs, and innovate by predicting future trends and customer behaviors.

What are the challenges in implementing big data analytics tools? 

Big data can mean big problems. Managing huge datasets, ensuring data quality, and integrating new tools with your existing ones can be very challenging. Data privacy and security, as well as the need for skilled experts are also hurdles in the process.

What are the different types of big data analytics? 

There are four main types of big data analytics, including descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics helps understand what happened in the past, while diagnostic analytics explains why it happened. Predictive analytics forecasts future outcomes based on historical data, and prescriptive analytics suggests actions to take for optimal results.

How does big data analytics support decision-making processes? 

By analyzing large datasets, businesses can identify trends, forecast outcomes, and evaluate the potential impact of different strategies. This leads to more accurate, timely, and effective decisions that drive business success. In short, data analytics are essential for business success.

What are the latest trends in big data analytics? 

It’s no secret that the use of AI in marketing analytics is growing fast. As a whole, the recent trends in big data analytics include the increased use of predictive analytics with AI and ML, the adoption of cloud-based analytics platforms for greater scalability and flexibility, and the growing importance of data privacy and security in analytics practices. 

Businesses are also increasingly focusing on data integration in real-time analytics to gain immediate insights and improve agility.

Conclusion 

In terms of leveraging data for the success of your business, big data analytics tools are a great help. From improving decision-making processes to optimizing marketing strategies, these tools provide the insights needed to stay competitive in today’s data-driven landscape. 

Whether you have a small business or a large enterprise, there’s a big data analytics tool on this list that can help you achieve your goals.

Key takeaways 

  • Big data analytics involves processing large datasets to uncover patterns and insights hidden in data.
  • Tools for big data analysis help companies optimize operations, personalize customer interactions, and even boost profitability.
  • The key features you should look for in a tool are handling large data volumes, scalability, ease of use, integration, cost, and security.

Still looking for the perfect big data analytics tool for your brand? We might be a good match. Don’t hesitate to learn more about Adverity’s offerings and see how our marketing analytics solution for agencies can transform your data strategy. 

To see these tools in action, schedule a demo today.