6 top Data Analytics trends: Unveiling tomorrow’s standards

Data Analytics is a fundamental part of running a business today. 

With essential, real-time information available right at fingertips, organizations find it easier to plan ahead and navigate disruptions to gain a sustainable edge.

And, with ongoing advancements and progress in the domain, we anticipate Data Analytics to continually revolutionize how businesses operate and make decisions. Technologies like Artificial Intelligence, machine learning, and cloud computing are undergoing constant evolution, giving rise to an array of Data Analytics trends.

We’ve expanded on the top Data Analytics technologies that are driving a tidal business change in 2024. From augmented analytics to synthetic data, here’s a low-down on what’s pushing the envelope of Data Engineering this year.

Data analytics: What it is and why it matters

Data Analytics are basically insights derived from a versatile range of data sets. These insights uncover details about trends, correlations, patterns, and anomalies within Data, leading organizations to take necessary action as required and ensure optimal levels of operational efficiency, productivity, and continuity.

While these insights facilitate informed decision-making and strategic planning, they also offer additional benefits to organizations.

• Increased operational efficiency: Optimize processes, reduce waste, boost productivity.
• Enhanced customer insights: Understand preferences, tailor offerings, improve satisfaction.
• Competitive edge: Analyze trends, stay ahead, adapt quickly.
• Risk identification: Predict potential issues, mitigate risks, ensure stability.
• Innovation driver: Identify opportunities, foster creativity, develop new solutions.
• Cost reduction: Identify inefficiencies, streamline operations, save resources.
• Compliance assurance: Monitor adherence, ensure regulatory compliance, mitigate legal risks.

Safe to say, Data Analytics play an increasingly important role in transforming modern businesses, and with continuous influx of innovations, we see a slew of trends shaping the data analytics future. 

Let’s explore the top 6 Data Analytics technologies trends to watch out for in 2024.

6 emerging trends in data analytics technologies

Let’s dig right in to explore the leading trends in Data Analytics, empowering enterprises with live insights while maintaining a low cost of ownership. 

1. Augmented analytics: A new dawn of hyper-efficiency

The fusion of Artificial Intelligence & Machine Learning with Data Analytics is paving the way for Augmented Analytics in 2024. 

These augmented insights will not only help uncover insights without needing specific context through the application of Natural Language Processing (NLP) and ML but also make sense of any unstructured data, such as phone calls.

Traditionally, an army of professionals was required to drown in data, discover and define the patterns, and model their findings. However, with the inception of modern, mature ML models, the old, manual-intensive ways are superseded by automation.

These ML models can delve into any strain of data, ascertain patterns across millions of edge points, point out anomalies, and instantly alert teams - without a human having to lift a finger.

AI-backed augmented insights are pacing up to define the Data Analytics future. Research says the market of such insights will grow by 26% every year, hitting over $32 billion by 2027.

2. Data observability: Illuminating the path to higher-quality data

In the year 2024, data observability comes to the fore as one of the significant trends in data analytics.

Data observability makes a case of higher-quality, consistent data. It’s a newfangled phenomenon, advocating the use of advanced tools and technologies to monitor and track the quality and integrity of data and its performance thereafter.

As an emerging buzzword in the industry, it focuses on rooting out and rectifying data errors and inconsistencies in real-time, ensuring data quality and accuracy. 

Data observability, as it grows popular, rekindles the flame for data veracity. The approach is driving organizations to reinforce trust in Data-driven processes and optimize data workflows to derive accurate, meaningful insights for informed decisions. We expect it to become a bigger, more prominent data analytics trend in 2024. 

3. Data mesh architecture: A step towards achieving data democracy

Data mesh is picking strong momentum to be one of the shape-shifting Data Analytics trends in 2024. 

A Data Mesh architecture encourages self-service analytics through decentralization of data ownership and management. It views data as a commodity and creates domain-oriented data teams. 

When a Data Mesh is live, it delegates the ownership of data across every team within the scale of an organization, allowing it the flexibility and autonomy to manage data products per their requirements. There’s no centralized team having complete control. Teams become the owners of data they access and bank on. 

In a model driven by Data Mesh, teams have the option of using domain-based tools and technologies, contributing to enhanced innovation, experimentation, and decision-making. Cost efficiency is another plus point, which is achieved by relieving storage systems, enabling interoperability, and ensuring that security and regulatory compliance is met.

4. Metadata-driven data fabric: Getting the Context in Focus

Gartner defines metadata as ‘Data in context.’ 

At its simplest, metadata describes the characteristics, conditions, and backdrop of data. Classified as ‘administrative,’ ‘descriptive,’ and ‘structural,’ it is stored in databases, files, or specific repositories that streamlines and simplifies data discovery, governance, lineage, and quality. 

Data fabric refers to a centralized architecture, integrating and managing the influx of data from various sources and facilitating its dissemination at scale for a unified view.

Together, these forces are forming the new frontier for Data Analytics technologies in 2024. Metadata is emerging to become a critical component of data fabric architectures. It performs a significant function within the data fabric, helping with data discoveries, governance enforcement, lineage tracking as well as quality monitoring. 

Data fabric and metadata, the two leading data analytics trends, intelligize the business core and produce continuous analytics, resulting in improved and simplified Data Management practices. 

5. Synthetic data: Leveraging artificial information to solve real-world problems

Gathering data is easier said than done. It’s a tedious, time-intensive, and expensive process, and some organizations aren’t equipped with resources to capture higher-quality data needed for AI & ML training. 

Here’s where synthetic data steps in as a game-changer. Synthetic data is artificial, algorithmically-created information harnessed to solve real-world, on-ground problems. The best part about synthetic data is that it can be produced on-demand, in any scale or volume, from anywhere to train ML models. 

Another selling point revolves around security and privacy. Synthetic data is fake information, so even if it gets breached, there’s no risk involved. It was never genuine to begin with.

In 2024, we anticipate synthetic data to climb new charts of popularity. According to Gartner, synthetic data is expected to constitute 60% of the data utilized by AI and analytics solutions by 2024.

It’s expected to be one of the biggest Trends in Data Analytics, feeding the next generation of algorithms and transforming the world as we know it. 

6. DataOps: Building seamless, transparent, accessible, secure, and collaborative data pipelines

We see DataOps solidifying its stance as one of the key Data Analytics trends in 2024. 

It’s common knowledge that organizations generate an avalanche of data every passing hour. With data converging from all across the business ecosystem, organizations encounter challenges in managing it. 

DataOps provides a systematic approach to handle this influx, streamlining data workflows across the quarters and paving the way for operational efficiencies. It’s a holistic approach, enabling integration between people and processes and making collaborations smoother for faster, more efficient decision-making.

By dismantling the silos and freeing trapped value, DataOps ensures a healthy data lifecycle where decision-makers can collaborate, leverage faster time-to-insights, and take timely decisions for overall growth and profitability of the company.

While DataOps has already consolidated its niche, we anticipate it to become a leading formative force in the market of data analytics technologies. 

Data analytics trends: Decoding 2024’s forces of change

In today’s uber-competitive times, no business can run without data.

However, at the forefront of data deluge, the success of any business is associated with how effectively it cradles data and leverages the unprecedented power of it.

These trends, from augmented analytics to DataOps, can empower such a business with cutting-edge measures to compete effectively and transform at pace, even in the face of disruptions. These forces, as the right hand, can help them operate, grow, and scale dodging every obstacle along the way. 

Adapting to these trends while staying vigilant about security and compliance is the golden rule for organizations, wanting to reap the full benefits of their data in 2024 and beyond.