Posted on

Using Machine Learning to Automate Data Cleansing

According to Gartner’s report, 40% of businesses fail to achieve their business targets because of poor data quality issues. The importance of utilizing high-quality data for data analysis is realized by many data scientists, and so it is reported that they spend about 80% of their time on data cleaning and preparation. This means that they spend more time on pre-analysis processes, rather than focusing on extracting meaningful insights.

Although it is necessary to achieve the golden record before moving on to the data analysis process, there must be a better way of fixing the data quality issues that reside in your dataset, rather than correcting each error manually.

Posted on

Fighting Covid-19 With The Power of AI

All in the world was going well, when suddenly, one day, everything came to a halt with the spread of the deadly COVID-19 pandemic. Not just a city or a country, but the whole world was in trouble because of a virus, having no treatment spreading at an unprecedented pace and claiming lives.

It was soon realized that such a powerful virus required something even powerful to combat its spread till a vaccine or a drug was found and thus, promising technologies like Artificial Intelligence and Internet of Things were given a consideration which did offer a huge helping hand as was desired.

Posted on

7 Great 2018 Advancements in Enterprise Knowledge Graphs

While the term “Knowledge Graph” is relatively new (Google 2012), the concept of “representing knowledge as a set of relations between entities — forming a “graph” — has been around for much longer.

2019 marks, for example, the 20th anniversary of the publication of arguably the first open standard for representing “Knowledge Graphs” designed with web distribution and scale in mind (The W3C RDF standard).