Enterprise Data Strategy: Unveiling the Top 5 Big Data Analytics Trends for 2024

As the world embraces a digital-first approach, data analytics has become essential for businesses to understand customers and improve their services. Subsequently, researchers forecast the global big data analytics market value to surpass $650 billion by 2029. Do you want to be ahead of your competitors by leveraging the most beneficial data analytics trends? Then keep reading!

TEAM data analysts share a quick rundown of their top 5 analytics predictions for 2024 and how they will reshape the future of global businesses.

Top 5 data analytics trends for 2024 and beyond

Experts predict that the amount of information created each day globally will hit 180 zettabytes by 2025. So, below, we will explore the best significant data processing trends you can leverage today to build a strong data strategy to ensure your business continuity.

#1 Data analysis automation to minimize all things manual

Companies need tools to analyze those immense numbers of generated data quickly and accurately. This is where automated data analysis comes in. It's a technology that uses algorithms and machine learning to analyze data, visualize it, and extract valuable insights. The combination of cutting-edge instruments lets you process large chunks of information in seconds and with higher accuracy, minimizing human involvement and errors and increasing operational productivity.

Regularly using automated data workflows, you can instantly generate and update reports and improve data quality, simultaneously enhancing your enterprise AI strategy. So, this year and beyond, automation in extensive data analysis is on the rise after it conquered almost all other industries.

Prompt results will, in turn, empower you with the capabilities required to stay ahead of the competition and boost ROI. Moreover, APA will drive further digital transformation across other sectors and support innovative developments in inventions like driverless vehicles.

#2 Edge analytics (EA) to help you capitalize on networks

Centralized data processing centers and extensive server rooms receded into the past since Gartner predicted that over 75 percent of enterprise-generated data would be processed with edge computing solutions by 2025. Meanwhile, Big Tech companies like Google and Amazon have capitalized on edge data analytics for years. So, EA is the next big thing in data analysis. Particularly because it provides processor-intensive, real-time business insights on the network's outer edge, making data accessible to people outside of it.

Another significant EA advantage is that it empowers your organization with higher flexibility and agility to adapt to a dynamically changing market on the go. EA ensures that your insights collected from dozens or hundreds of connected devices are more manageable, accurate, observable, and obtained faster. Cloud-based architectures add lower costs, less physical space, and bandwidth constraints. What do you get? A perfect decentralized solution to transform piles of data analytics, AI findings, and decision intelligence into the value streams of your organization.

#3 ML and AI-enabled processing for the absolute win

Global business leaders leverage AI to improve corporate data visualization processes to get more informative and accessible insights. Meanwhile, there is another niche Industry 4.0 tech that can propel your organization to new heights. Take a closer look at machine learning algorithms. They can automatically learn from all your data, self-improve, and make accurate predictions. You can apply digital analytics augmentation in various daily activities, and your data analysts will thank you.

A quick list includes:

1. 1.Outputs mean products, services, or measurable value a company delivers
2. 2.Finding patterns in collected information
3. 3.Generating actionable recommendations for decision-making
4. 4.Extracting valuable insights from massive piles of data
5. 5.Formulating efficient and effective internal processes
6. 6.Systematizing real-time and historical information
7. 7.Interpreting and transforming unstructured data
8. 8.Gaining insights from videos and audio files
9. 9.Creating a personalized customer experience
10. 10.Assess business risks based on the collected data

In the next decade, the importance of AI/ML tools for SMEs and large enterprises' success will grow tenfold as consumers seek augmentation. Combining AI and ML analytics solutions with your BI tools allows you to monitor, cleanse, and analyze the most complex types of big data. Having 95 percent accurate, powerful results after processing it will help you uncover new value streams that come with it. Take ChatGPT as an example—Large Language Model platforms like this will revolutionize the global data sphere. So, when creating your next-gen data strategy, remember that augmented analytics protocols improve your operational performance and the quality of data you need to train your enterprise systems.

#4 Data Fabric and as a Service crusade toward democratization

The adoption of cost-effective hybrid multi-cloud systems is on the rise, with more than 70 percent of businesses opting for virtualization. So, to keep up with innovations, you'll need a robust data fabric (DF) framework to standardize the best data management practices and maintain consistent analytics flows. DF architecture offers a unified end-to-end solution that connects large data pipelines and cloud networks. It helps you collect, store, organize, interpret, and analyze vast amounts of data with intelligent automation.

This approach lets you share information across applications and platforms without third-party software tools. Moreover, data fabric is an easy-to-use and repurpose self-service analytics instrument that improves how you use data within your company. It reduces operational data management workloads by 70 percent. Executives can rely on DF tech to understand their business direction better, take relevant actions, and make more informed decisions quickly.

Diving deeper, businesses will demand more democratized data analytics in 2024, accessible to all who need it for running operations smoothly and intelligently. So, data fabric will play a key role in data democratization that will, in turn, empower entire workforces.

Plus, since we've mentioned the rapid migration of businesses to the cloud, we must also emphasize that it leads to the growing popularity of the Everything as a Service trend. It allows you to cut expenses significantly, access cloud data sources “anywhere,” avoid building your own data storage and processing operations, and more.

#5 Big data quality and security analysis becomes imperative

Did you know that data breaches caused the exposure of around 15 million data records worldwide during the third quarter of 2022 alone? Moreover, according to IBM, the global average cost of a data breach is $4.35 million, while the average cost of a data breach in the US is almost $10 million. Unfortunately, as digitalization keeps advancing rapidly, so will cybercrimes. So, your main goal is to safeguard your corporate data under the most modern security protocols.

Steps to take when developing your big data security strategy for 2024 and beyond:

1. 1. Outline an enterprise cyber defense action plan.
2. 2. Install big data analytics tools to collect, store, and analyze real-time security data.
3. 3. Implement data encryption and access controls.
4. 4. Use predictive analytics to identify your cyber vulnerabilities.
5. 5. Enforce ethical data practices and transparent compliance protocols.
6. 6. Train your employees to follow all security standards and BYOD policies.
7. 7. Improve your data observability, accessibility, and quality.
8. 8. Define cyber risk mitigation steps and the roles responsible for triggering them.

To avoid becoming a victim of a data breach cybercrime and paying enormous legal fees, we recommend modernizing your company's cyber defense. Our professional tip is to leverage big data security analytics to detect hacks in time and combat them effectively. Also, ensure that you use only high-quality data in your daily operations. Poor quality leads to bad business decisions, slow incident response, and business capacity losses. Quality metrics and data governance frameworks will help you operate based on timely insights and maintain data security and privacy.

The state of data analytics in the era of Industry 4.0

The world generates more than 2.5 quintillion bytes of various data daily. Let's admit it's a staggering amount that should be collected from different sources, sorted, organized, transformed, and analyzed to extract actionable insights for successful business decisions. We have data scientists and analysts, ML algorithms, digital statistical tools, and automation platforms to help us understand complex data sets. So, trusting your gut is an asset, too, but it's not enough anymore as the world becomes one synchronized digital-first organization.

In the last five years, companies globally have started to rely heavily on data for decision-making and have significantly boosted their performance. The expected revenue of the global big data market is $273/4 million by 2026. That's because timely business insights and intelligent analytics tools are now essential for any forward-looking executive. Analytics is the tool that helps improve customer experience, predict demand and supply, and develop new services or products to unlock additional value streams.

The analytics sector keeps evolving rapidly to introduce new technologies, approaches, and methodologies that offer more secure and accurate access to insights. Moreover, you can get more intelligent analytics much faster by benefitting from emerging data processing trends. For instance, 27 percent of executives profit from their companies' significant data initiatives.

Aside from the top five described in this article, you should also closely monitor data governance over the next 12 months. Governments will continue adding laws to regulate the use of data for personal and business purposes. Gartner analysts forecasted that 65 percent of the world’s population will be covered by GDPR-similar restrictions by 2023. So, expect more GDPR, PIPEDA, and PIPL-like legislation that you will be obliged to comply with in the next few years.

It's in your best interest to create robust enterprise data analytics frameworks. High-quality data is now the differentiator between winners and laggers. Your only chance to remain resilient is to opt for a data-driven business model that will empower you to manage risks proactively, even during uncertain times of pandemics, wars, and economic recession.