It is a well-known fact that Data Analytics has experienced significant growth and transformation in recent years. The increasing availability of data, technological advancements, and the ever-ceasing demand for data-driven insights mainly drives this.
Data analytics provides opportunities for enterprises to enhance operational efficiency, optimize business processes, and reduce costs. It greatly helps in identifying bottlenecks, facilitating workflows, and boosting productivity.
Especially, the Middle Eastern countries like the United Arab Emirates, Kuwait, Qatar, etc are facing an upsurge in the demand for data analytics. This is mainly due to the continuous development of smart cities in the Middle East and their rising reliance on data analytics for optimizing security, enhancing transportation, managing resources effectively, and boosting the overall quality of life. Also, the increasing usage of data analytics in the healthcare sector positively influences the market.
However many Middle Eastern organizations and enterprises across the globe face certain challenges while embracing data analytics. These hurdles need to be overcome to attain data success.
In this blog, we can see those challenges and some remarkable data analytics trends to look for in 2024.
Top Data Analytics challenges that businesses face
Bringing extensive data to big data platform
These days organizations need to address a massive quantity of data daily. Loading and transforming information into the data warehouse becomes challenging due to multiple data sources. Here, exceptional data engineering skills become essential to make data accessibility seamless.
Gaining meaningful insights using Big Data analytics
Competencies are big barriers when it comes to producing meaningful insights using big data. The lack of structured data engineering methods is the technical barrier to obtaining insights.
Uncertainty of data management landscape
There are a lot of competing technologies available within every technical area e.g. visualization tools, ETL tools, database technologies such as OLAP/OLTP, etc. Out of many options available, the ultimate challenge is making smart choices while not introducing any additional risks to big data adoption.
Data storage and fast retrieval
As mentioned above, with the widespread business operations and verticals, businesses are producing large volumes of data which will be further increasing day by day. The data storage and data accessibility become significant and create a requirement for data warehouses and data lakes that can store, process, and retrieve information whenever required. The problem arises when a data warehouse or data lake tries to integrate inconsistent/unstructured data from different sources and it encounters errors.
What is coming next in Data Analytics in 2024?
Data Mesh Architecture
It is a decentralized approach to data management that primarily focuses on making data usable and accessible for all users. Data mesh architecture takes a more scalable and flexible approach than traditional data management architectures. It will be a very good choice for managing complex and large data sets while still providing instant relevant data.
Continuous Intelligence
It aims to empower action by utilizing real-time information. The goal is to leverage the flow of data for decision-making. This year, businesses will embrace using data to make prompt informed decisions. This will eventually enable them to respond to changing circumstances and evolving opportunities. Some key aspects of Continuous Intelligence include data processing and analysis, real-time data ingestion, automation, integration with business processes, and prescriptive and predictive analytics. To say simply organizations will be able to enhance business operations and drive better decision-making.
Quantum computing
Although still in its early stages quantum computing has extensive potential to address complex challenges in data analysis. This year we can expect to witness more testing and research in this field for many industries. Its features can be utilized to help with certain kinds of computations more effectively than classical computers. Key concepts of quantum computing include entanglement, superposition, quantum gates, quantum supremacy, quantum algorithms, and quantum error correction.
AI-powered data analysis
AI is changing global business operations and its introduction to big data has greatly enhanced data visualization and analysis and improved human data handling capabilities. AI-powered systems enable us to make faster and more flexible decisions while adapting to change.
Final thoughts
As said above the future will definitely demand maximizing value through data which will be held high in all organizations. So, organizations can overcome the key hurdles and implement the trending data analytics concepts by getting a comprehensive data analytics service from a prominent IT service provider.
Techmango is a well-known IT service-providing company that delivers best-in-class data analytics services for businesses of all types and sizes. Our team has immense expertise in various advanced tools and technologies like Tableau, Talend, Informatica, Power BI, Azure, Pentaho, AWS Athena, AWS Glue, Azure Data Factory, Microsoft SQL Server, Apache Spark, Jaspersoft, Sisense, Rackspace, QlikView, BusinessObjects, Oracle, etc to deliver astonishing data analytics solutions.
Techmango can act as your Data analytics partner for
- Trusted technology Offshore partnership
- Center of Excellence (CoE) for Data analytics services and solutions
- IT staff augmentation/ Resource provider for data analytics services
Without any further delay reinforce your business growth right away with industry-leading data analytics services from Techmango.
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