Nowadays, businesses can produce data analytics based on big data from numerous sources. Once they acquire access to all of the requisite data sources for analytics and business intelligence in order to make better decisions. The transfer of this data is facilitated in a streamlined manner by different data ingestion strategies.
What Is Data Ingestion And Why Is It Essential?
By Allen Victor on Aug 31, 2022 5:38:46 PM
Top 5 Data Science Trends For Businesses Today
By Allen Victor on Aug 29, 2022 3:45:00 PM
Businesses can save plenty of time and millions of dollars when they use data science to better understand and improve their processes. With the age of the democratization of data, there have been several emerging trends defining enterprise data manipulation and data engineering.
Why Data Engineering And AI Are Mutually Beneficial
By Allen Victor on Aug 24, 2022 5:40:00 PM
Artificial Intelligence (AI) and data engineering are closely interlinked. On one hand, making sense of unstructured data is the process known as data science or data engineering. On the other side of the same coin, AI-programmed computers have the ability to learn as they go, getting better at solving particular sorts of problems as they accumulate more data. So one cannot exist without the other.
The Role of MLOps in AI Application Development
By Archna Oberoi on Aug 23, 2022 6:41:00 PM
Machine Learning (ML) is an application of Artificial Intelligence that has the maximum number of use cases, in almost every industry. Healthcare, automobile, marketing, finance, agriculture, retail- all of them are leveraging the power of ML to automate tasks and bring agility to operations.
Multi-Cloud Management: Challenges, Tools, and Best Practices
By Archna Oberoi on Aug 16, 2022 5:19:00 PM
Migrating to the cloud is the new normal for businesses of all sizes. Based on availability, compliance, performance, sovereignty, and other technical factors, businesses are making a choice for a relevant cloud services provider.
Software Testing Services: Understanding User Acceptance Testing (UAT)
By Archna Oberoi on Aug 9, 2022 3:50:00 PM
In an SDLC, there are several testing frameworks that help to assess if the application is progressing in the right direction. It could be in terms of usability, security, compatibility, performance, integrations, etc.
Speech-To-Text: How Automatic Speech Recognition Works
By Allen Victor on Aug 2, 2022 4:37:19 PM
Speech recognition is a technology that has been going through continuous innovation and improvements for almost half a century. It has led to several successful use cases in the form of voice assistants such as Alexa, Siri, etc., voice biometrics, official transcription software, and the list goes on. So what really is Automatic Speech Recognition and what are the underlying technologies that enable it?
What Does A Salesforce Administrator Do For Enterprises?
By Allen Victor on Aug 1, 2022 4:54:21 PM
The business landscape of the modern world is heavily customer-centric with marketing, sales, and customer support at the center of operations. Salesforce is the most sought-after Customer Relationship Management (CRM) software intended for these purposes. There are a variety of roles and responsibilities in an enterprise's Salesforce team and the Salesforce Administrator is usually at the helm of it.
Top 5 Ways FinTech Uses Biometrics Technologies
By Allen Victor on Jul 27, 2022 4:53:34 PM
Increasingly today, Financial Technology (FinTech) companies have been using mobile devices and applications as promotional platforms. Biometrics technologies are a necessary addition to the FinTech domain and have the critical task of enhancing security through the accurate identification and verification of the customer's identity.
How Does NLP Fully Leverage Unstructured Healthcare Data?
By Allen Victor on Jul 26, 2022 12:19:30 PM
A majority of healthcare data today, about 80% of it, happens to be unstructured. Most sources used for aggregating Electronic Health Records (EHR) require a considerable amount of pre-processing because most of them are not machine-readable. Natural Language Processing (NLP) and various Machine Learning (ML) techniques can, however, unlock all the potential enmeshed in unstructured data.