Big Data, Cloud & DevOps

 SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise. What is SSDP? SSDP or Self-Serve Data Preparation is a crucial component of Advanced Data Discovery. With self-serve data prep, data analytics moves

The history of digital technology has largely been one of denial followed by disruption. First came the concept of the productivity paradox, which noted the limited economic impact of digital technology. When e-commerce appeared, many doubted that it could ever compete with physical retail. Similar doubts were voiced about digital media.Today, it’s hard to find anyone

Data integrity is the consistency, accuracy, and validity of data throughout its useful life. Compromised data, in any context, is not useful- and can cause harm. There are numerous ways in which data integrity can be compromised.Data integrity is critical to just about every aspect of a business, but when it comes to the human resources

When our team’s project scored first in the text subtask of this year’s CALL Shared Task challenge, one of the key components of our success was careful preparation and cleaning of data. Data cleaning and preparation is the most critical first step in any AI project. As evidence shows, most data scientists spend most of their time — up to 70% — on cleaning data.In this

You can’t buy DevSecOps—the practice of putting security practices into your DevOps methodology—but there’s marketing noise that may make you think that you can buy your way into DevSecOps. When you’re moving your enterprise teams to a DevSecOps model, you need to see it as more than just a technology stack. Here’s why. Security Becomes Part

Homomorphic encryption solves a vulnerability inherent in all other approaches to data protection Imagine if you work in the financial services industry — or, maybe you already do. Every day, your organization handles a lot of personally identifiable information (PII) and financial data — information that needs to be encrypted both when it is stored

To err is human.The important thing is to look at our mistakes. And learn from them.A data scientist needs to be critical and always on a lookout of something that others miss.But sometimes in our day to day job and coding perse, we get lost in our train of thought and fail to look at the overall

A symptom of the unhealthy relationship between cyber security and large firms As we reach one of the high points of each year’s conference season, one has to reflect once more on the staggering number of products and vendors active across the cybersecurity space. Once again, they will line up in their hundreds at Infosec

Sometimes working with big data resembles dining at an “all-you-can-eat” restaurant: you get too much food and are busy swallowing it all without thinking of its quality or your health. You should never forget, though, that data is a double-edged sword and requires cautious handling. If gives businesses new power to organize, operate, predict and

Every once in a while, a technology comes along with so much potential that people can’t seem to stop talking about it. That’s fun and exciting, but it can also be confusing. Not all of the people who opine really know what they’re talking about and, as the cacophony of voices increases to a loud

Everywhere there are smart devices collecting and sharing data. It is estimated that by 2020, there will be more than 50 billion such devices. Can you imagine the amount of data that will be produced in the upcoming years?According to the recent findings by Statista, it is predicted that 50.5 zettabytes of data will be