As a business professional, you are probably responsible for making many important decisions, whether it be something as simple as drafting a social media post for the company account or coordinating the arrival of a revolutionary product to market. But with the burden o
In 2023, the international business intelligence market size is aimed to register a value of US $28,216.8 million. It is aimed at growing to $56,200.9 million by 2023. The market value of mobile BI is predicted to reach a CAGR of 22.43% between the forecast period of 2021
With the introduction of ChatGPT-3 and DALL-E2, the majority of investors started showing interest in businesses building generative AI. Moreover, the fact is generative AI is not enough to reach the needs of the AI revolution. The success of predictive models is relevant
Latest surveys report that the use of predictive analytics in marketing has increased after realizing its importance at the business level. Organizations looking to stay in a dynamic world use data analysis to predict upcoming shifts. Despite being predominantly used, the
Both eCommerce and retail companies struggle to track changes in customers’ preferences and constantly update themselves to serve accurate recommendations. The solution to such a problem is the use of AI-driven product recommendation engines. Both retail and eCommer
While analyzing data, you must ensure that it has no errors. Mistakes give a false impression of the overall statistics of the data. To cut down errors, you need to prepare your data. Here's how.
With the voluminous inflow of big data in every enterprise today, data chaos is a reality. Managing data is a must requirement.
A major challenge facing organizations today is data quality. As data evolves, it becomes more complex and more fragmented. The result is that data can be difficult to understand and use, which can result in inaccurate or incomplete information. Data mesh can help address this issue by creating a network of data sources.
Whenever a business employs data analytics to make decisions, the process of data ingestion is crucial. The lack of data prevents businesses from understanding their customers, improving their products, or making informed decisions about how to run their businesses. For analysis, data ingestion involves collecting, cleaning, and storing data. Data ingestion is a complex process that requires careful planning and execution.
