Big data, huh? No matter where you look, there it is! And this seeming omnipresence is not without reason, i.e., the technology does indeed play a vital role in the world today. Defined as an amalgamation of different tools to gather and closely analyze data, big data delivers highly valuable insights and analysis. As you can imagine, this ability has made it highly beneficial to, well, literally every industry and business on the face of Earth. That holds for the manufacturing industry…

In our previous article — 5 Challenges to be prepared for while scaling ML models, we discussed the top five challenges in productionizing scalable Machine Learning (ML) models. Our focus for this…

Machine Learning (ML) models are designed for defined business goals. ML model productionizing refers to hosting, scaling, and running an ML Model on top of relevant datasets. ML models in production also need to be resilient and flexible for future changes and feedback. A recent study by Forrester states that improving customer experience, improving profitability & revenue growth as the key goals organizations plan to achieve specifically using ML initiatives.

Though gaining…

Big data has come to play an essential role across the entire spectrum of industries in the world today, including real estate. In fact, in real estate, this novel technology has an exciting role to play. You see, real estate is inherently complex, thanks to the countless factors involved; there’s the people, the local real estate market, and several other factors that affect it. As a result, it can be quite challenging too, say, determine the right price or rent for a given property.…

Big data analytics in the healthcare industry today is evolving into a promising field for delivering real-time insights from very large data sets. Plus, it also helps improve outcomes while reducing costs.

The trending digitization is leveraging the potential of data analytics and business intelligence.

According to Industry experts, the AI health market is to…

Introduction:

Here’s a fun fact; An average human being (probably an adult) makes close to 30,000 conscious decisions every day. This isn’t entirely true though, in fact, I just made that number up. I could be right because if you think about it, how many decisions would you say you make on a day to day basis? Depending on who you are the above obviously varies widely and you know best. We all…

Introduction

Artificial neural networks are based on collection of connected nodes, and are designed to identify the patterns. They are part of deep learning, in which computer systems learn to recognize patterns and perform tasks, by analyzing training examples. For example an object recognition system can be fed to thousands of labeled images of houses, cars, traffic signals, animals etc. and would…

Just about every company worth its salt today uses data and analytics to better understand their customers and better meet their needs.  For some companies, such as Google, Amazon and others, data science is the very foundation of their business model - but these companies use data analytics in service of their broader core mission.  The universe of public companies that actually provide data and analytics solutions is far smaller and harder to define, but includes industry behemoths such as…

In the era of the Internet, the ability to crunch large amounts of data and process it with speed and efficiency has become essential for businesses to survive. But you try sitting down and going through all that data by hand: you'll get done sometime in the year 2050 if you're lucky.

That's where machine learning comes to the rescue. But…

Overview:

This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes.  

Aligning goals:

Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the…

Recently Netflix launched Rs 199 ($2.8) mobile-only monthly plan in India. CyberMedia Research (CMR) reported that after the release of the new mobile plan, Netflix now has the potential to reach 3.7 million subscribers as compared to the earlier number of 1.3 million subscribers in India by the end of the year. This increased subscriber count…

The online food delivery business has taken off in the past few years — that much everyone knows. But do you know why this industry has noticed such rapid growth in demand and popularity? It is because of the utter convenience they deliver. Today’s customers come with high expectations, and this industry seems to have checked all the boxes one needs to; well, save for one. Delivery time — this continues to remain a sore spot for most customers who engage with online food delivery businesses.…

We’ve written a lot about finding and preparing data lately. But that’s only the beginning when it comes to extracting value from it. When organizations begin flowing external data through their organization, the various issues associated with data sharing start causing problems. Some of these issues include:

• Controlling permissions and data access, including sharing partial/filtered views or picture-in-picture data
• Accurately tracking changes to data and monitoring how…

Industry 4.0 or the fourth industrial revolution is predicted to revolve around data. Organizations that will thrive this revolution will be the ones that will realize the value of data as their corporate asset and make smart technology choices to make data-driven decisions. For the organizations of today to get future-ready, having smart analytical applications to bring together data from multiple sources, form a meaningful dataset, and accelerate the…

What is ETL?

Put simply, an ETL pipeline is a tool for getting data from one place to another, usually from a data source to a warehouse. A data source can be anything from a directory on your computer to a webpage that hosts files. The process is typically done in three stages: Extract, Transform, and Load. The first stage, extract, retrieves the raw data from the source. The raw data is then transformed to match a predefined format. Finally, the load stage…

We will talk about two chief technologies that deal with data namely Business Analytics and Data Science. The latter is specific to customer choice, geographical influences concerning the business, and the former deals with business issues that relate to profit, cost, etc. …

The world is on the constant lookout for technologies that can help us further improve how we go about not only our daily lives but how we conduct business as well. And this search has led us to highly valuable resources: Geolocation and big data. We know the world is brimming with data, which makes it vital to use technologies that can help us sort through this data and make some sense of it. That’s where big data comes in — allowing us to extract value from the abundance of data. It is…

You’re a data scientist, but you didn’t end up in the data science industry.

Are you worried about not making it?

Fret not, we’ve got multiple career options molded perfectly for you.

Ever since data science and big data analytics became the buzzwords in the industry, career options in these fields never went amiss. Job roles in both the data science and the big data analytics industry continue to reign as some of the most coveted jobs a tech professional could…

Deep Learning is a major branch of Machine Learning we have heard so much about.With or without our knowledge, deep learning is strategically influencing our day-to-day decisions.

The past few years have witnessed a…