Mid-year top trends in Big Data and Data Analytics

The volume of data in enterprises continues to grow exponentially, and organizations have more than half of their data untapped and unused in real time for new business opportunities. In this article, we analyze the key trends in data and analytics that are part of this year’s mainstream in enterprises and how to approach new solutions based on better data governance and management.

Today, companies are increasingly using the top trends in big data analytics to make strategic decisions, but there is still a lot of untapped potential. Without further ado, the volume of data is growing exponentially and every organization needs to be able to scale and manage it properly. In fact, according to Statista, 328.77 million terabytes are created every day.

Beyond this panorama, industry reports indicate that only 57% of the data collected by organizations is currently being used. This means that a staggering 43% of collected data remains unused. This percentage of untapped data represents a significant opportunity for organizations. Untapped information could contain valuable insights that could drive innovation, improve efficiency, and optimize operations. However, it also presents a significant challenge for organizations to find ways to manage, analyze, and derive value from this vast amount of raw data. And there is a clear shift toward industry-specific, customized big data and AI solutions, recognizing that each industry has unique needs but has yet to find the best way to meet them.

The evolution of leadership roles is a notable change in data analytics for 2024.

A Thoughtworks survey found that 87 percent of data leaders and technology executives agreed that people in their organizations are confused about where to go to solve data and technology-related problems or obtain relevant services. The same survey found that 79 percent of C-suite decision makers reported organizational roadblocks due to a lack of collaboration with other technology leaders. By 2024, we could definitely see a shift toward broader, more general technology leadership positions rather than specific, specialized roles like chief data and analytics officer.

Top Trends in Big Data Landscape in 2024

Among the top trends that will drive new challenges and opportunities for the data and data analytics landscape, the following can be highlighted:

1. AI-based real-time data insights:AI and ML automate data processing, allowing patterns to be identified and decision-making algorithms to be created faster than humans. Tools such as TensorFlow and IBM Watson are key to predictive analytics, enabling organizations to anticipate trends and behaviors. According to consulting firm Innowise, “AI solutions can automate up to 70% of all data processing work.”
2. ESG Reporting and Data Consolidation: Environmental, social and governance (ESG) reporting is becoming increasingly important, driven by new regulations and the demand for transparency. AI and machine learning play an important role in ESG data analysis, to ensure its legitimacy and combat greenwashing. Consolidating data from multiple sources into a single repository is critical for efficient analysis and reporting.
3. Quantum computing: Its ability to perform complex calculations at unprecedented speeds makes it promising for big data analytics, especially in areas such as drug discovery and climate modeling. Expect increased investment and research in this area, making it more accessible and integrated with big data technologies.
4. Democratization of data access: Data-as-a-Service (DaaS) platforms with intuitive interfaces are making data analytics accessible to non-technical users. This democratization fosters a more inclusive data culture within organizations and improves decision making.
5. Data Governance and Security: Tighter controls and modern approaches are critical in response to the rapid evolution of AI and its impact on data security. Automation, real-time governance, cloud-based solutions, and distributed models are key advances in this area.
6. Ethical considerations: Ensuring that data collection, processing, and use adhere to ethical standards is paramount. In this context, privacy, consent, fairness in AI, transparency, and using data for social good are critical.
7. IoT and Big Data Integration: Analyzing the vast amounts of data generated by IoT devices offers unprecedented opportunities to optimize operations and improve customer experience in sectors such as agriculture and healthcare.
8. Data Visualization: Tools such as Tableau and Power BI make it possible to translate complex data sets into understandable visual formats, improving decision making and information communication.

Top FAQs in Big Data & Analytics for the Next Semester

• How is AI used to improve big data analytics? AI automates data analysis, identifying patterns and trends that would be difficult for humans to detect. This enables faster and more accurate decision making in areas such as healthcare, finance, and marketing.
• Why is data governance important in the context of big data? As the volume and complexity of data increases, data governance is critical to ensuring the quality, security, and ethical use of data. It involves establishing policies, processes, and controls to manage data throughout its lifecycle.
• What are the key ethical considerations for big data? Ethical considerations in big data include ensuring privacy, security, and responsible use of data. It is critical to avoid bias in algorithms, obtain appropriate consent for data collection, and use data fairly and transparently.
• How will big data evolve in the future? Big data is expected to continue to grow in volume, velocity, and variety. Technologies such as quantum computing and AI will play an increasingly important role in data analysis, and a greater focus on data ethics and privacy is expected.

Impact of These Trends on Web Scraping and Public Data Extraction

Although these trends do not specifically mention Web Scraping, as it is a fundamental technique for collecting Big Data, we understand that the trends mentioned will also impact Web Scraping and Public Data Extraction, especially when it comes to large volumes of data that require increasingly sophisticated handling.

How will these trends directly impact web scraping practices?

We have already highlighted the exponential growth in the amount of data being generated every day. This trend is driving the need for more efficient and scalable Web scraping tools and techniques to handle the growing volume of data available on the Web.

In addition, the information presented highlights the critical role of AI and machine learning in big data analytics. This trend is also reflected in the field of web scraping, where AI is often used to automate data extraction, identify complex patterns, and improve the accuracy of the extracted data. The synergy between cloud computing and big data is also important. This synergy also benefits web scraping by providing scalable processing and storage resources in the cloud, allowing organizations to handle larger and more complex web scraping projects.

Finally, the industry sources consulted highlight the growing importance of privacy and security in the context of big data. This trend is relevant to Web scraping, as organizations need to ensure that they are collecting and using Web data ethically and in compliance with privacy regulations.

Web scraping will undoubtedly be an essential and irreplaceable technique for collecting and managing data in the near future.

Finally, what are some of the benefits of using Scraping Pros?

1. Leading your business: With our exclusive delivery of customized data, we guarantee accurate and up-to-date data that is perfectly aligned with your objectives, giving you a competitive edge in the marketplace and the ability to anticipate your competitors.
2. Real-time business growth: With Scraping Pros’ methodology, our clients can get to know the real problem in terms of risks, scope of growth and changing market dynamics. All this will help you design better strategies.
3. Know your customers and make future-proof decisions: Today, it is virtually impossible to make decisions without practical knowledge to develop strategies or action plans to ensure an upward trajectory. By hiring the services of Scraping Pros, you will be able to make these decisions, but you will also be able to better understand the expectations and needs of your customers.