Innovations in Predictive Analytics: ML and Generative AI
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 to the science fiction future that the majority of the customers want… Continue reading Innovations in Predictive Analytics: ML and Generative AI
Prasanna Chitanand | 09 Jun 2023
Predictive Analytics in Marketing: Hype or Reality?
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, there is a threat that it can become burdensome for users. The worldwide market for… Continue reading Predictive Analytics in Marketing: Hype or Reality?
Prasanna Chitanand | 05 May 2023
How to Boost Retail Revenue with a Product Recommendation Engine
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 eCommerce businesses adopt ML-based personalized product recommendations to select items to be displayed across the web or social… Continue reading How to Boost Retail Revenue with a Product Recommendation Engine
Prasanna Chitanand | 28 Apr 2023
The Importance of Data Preprocessing in Machine Learning
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.
Prasanna Chitanand | 29 Sep 2022
Data Chaos: What Is It And How Can It Be Resolved
With the voluminous inflow of big data in every enterprise today, data chaos is a reality. Managing data is a must requirement.
Prasanna Chitanand | 05 Sep 2022
All You Need To Know About Data Mesh
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.
Express Analytics | 06 Jun 2022
The Definitive Guide To Data Ingestion in Business
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.
Express Analytics | 21 Apr 2022
All You Need To Know About Synthetic Data
The world of business today revolves around data. While collecting synthetic data can be time-consuming and expensive, it can provide a cost-effective and efficient solution. The use of synthetic data is often a better option than collecting real data, since it can be used to test new products, validate models, and train artificial intelligence systems.
Prasanna Chitanand | 25 Mar 2022
Everything You Need To Know About XOps
There's a new buzzword in town, one that made it to the Gartner's list of key trends, too. Called XOps, it's roots lie in Development and Operations (DevOps). While DevOps falls short of achieving full automation, XOps, an umbrella term is used for a combination of IT tech. The ability to relate to customers in multiple segments is crucial for maximizing customer benefits. By analyzing data sets of similar customers, a class of artificial intelligence called machine learning can determine the most valuable customer segments. By using machine learning, customers can be segmented automatically since manual segmentation can take months or years.
Prasanna Chitanand | 19 Jan 2022
