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Top Trends In Big Data For 2024 And Beyond

Big data is demonstrating its worth to businesses of all sizes and in a variety of sectors. Businesses that utilize it extensively are experiencing observable benefits, such as enhanced operational efficiency, better visibility into dynamic business environments, and customer-focused product and service optimization. The new trend in 2024 goes like integrating data management with ERP Software.

The frontier of big data remains a significant force in technology’s rapidly evolving field. It influences data analytics, insights, and decision-making. Penieltech explores the top themes reshaping the Big Data landscape. This exploration anticipates a new era of data-driven greatness for organizations approaching 2024.

Stream Processing in Real Time for Big Data Insights

Sorting through the overwhelming amount of unstructured data can be rather difficult. Organizations need to handle data, whether it’s generated in near-real-time or the past. They must harness this data at scale and analyze it in real time. This is crucial for making sense of the information.

Stream processing is useful in this situation. Instead of processing data in batches, stream processing enables organizations to process data streams in real time. By continuously adding new events to the system as they happen and analyzing streaming data on demand, stream processing helps businesses to get insights from the data.

AI-Augmented Development

AI-augmented development is the major big data trend to be aware of. This will make development more efficient, which will free up time for improving your product or service rather than spending it on time-consuming chores.

Developers can use AI methods like machine learning to train systems. These systems can recognize patterns in data and apply them automatically. This proves especially beneficial for mobile apps tracking user behavior. They consider variables like location and the user’s current activity.

Automation and analytics powered by AI and ML

Over sixty percent of IT executives indicate that they intend to augment their expenditure on artificial intelligence and machine learning (AI/ML) solutions. These kinds of technology are helping organizations analyze large data and produce meaningful insights more quickly than ever.

In a medical example, human researchers may spend four to twenty-four hours analyzing specific neuron activity in a 30-minute movie. However, a machine learning-based algorithm can complete the same process in less than 30 minutes when used to analyze the video data.

Companies are automating massive data processing, filtering, cleansing, analysis, and more with AI/ML. AI technologies can automate 64% of data-gathering tasks and over 70% of all data-processing tasks.

Continuous Threat Exposure Management (CTEM)

Real-time threat intelligence is provided via the Big Data analytics platform Continuous Threat Exposure Management (CTEM). It evaluates a vast amount of data from multiple IT systems. These include virtual machines, cloud servers, and IoT devices. The goal is to identify emerging threats. The system provides actionable advice for organizations to protect themselves from cyber-attacks.

Platform Engineering for Sustainable Technology

Developers use a technology stack called Sustainable Technology Platform Engineering (STPE) to build networked applications on top of cloud infrastructure.

STPE allows developers to use open-source software and services for creating applications. It ensures runtime access to all dependencies. Additionally, STPE enables developers to work with various programming frameworks. They can modify the architecture of an application without needing to acquire new knowledge of languages or frameworks each time.

Data analytics and decision-making with data

ERP software stands for Enterprise Resource Planning. The ERP software system is designed to manage and track all the data associated with an organization’s daily operations. These processes include order processing, billing, accounting entry management, sales management, and resource planning.

ERP implementation offers numerous benefits. It centralizes data storage into a single tool. This improves information and action traceability. Data quality and reliability are enhanced. Productivity sees a boost. Due to the dependability and global perspective of the information, the business management streamlines.

Data analytics and data management enable us to value the huge flow of data or big data. ERP software assures the reliability and traceability of information while centralizing it to enable businesses to use it more effectively.

Data As a Service

Scalable and economical management is provided by data-as-a-service.

The data-as-a-service (DaaS) industry was predicted to surpass $10.7 billion in 2023. This category includes cloud-based solutions for data management, analysis, and collection.

Businesses can profit from big data without having to develop their data collection methods or costly storage platforms by employing DaaS. For many firms, managing their big data demands strategically and at a low cost is best achieved by working with a DaaS provider.

Approximately 40% of IT workers claim to use as-a-service platforms for data backup and storage. Non-technical employees can use user-friendly tools and apps using DaaS platforms, which enables them to improve their productivity and obtain new insights.

Wrapping Up

The landscape of big data trends in 2024 seems promising in terms of innovation and game-changing innovations. Accept the fundamental Big Data technologies influencing the solutions of the future.

Get in touch with Penieltech for innovative custom AI software and efficient big-data problem-solving. To drive success, use data to your advantage and navigate the future with intelligence.

Discover, customize, and grow your company with Penieltech—where creativity and knowledge collide.

We are an Official ERPNext Partner in UAE.

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