Big Data, Cloud & DevOps

Knowledge isn’t power. Almost everything we know is either currently on the internet, or will be soon. If we reach a stage when every person and machine has access to the same information, what will set you apart from the pack? Your power is through connection. One way you’ll stand out is by cultivating an

From bridging the talent gap to incubating the right culture to modifying the infrastructure, every small thing should be taken into account when companies plan to harness the power of any new technology. The digital world is here. Just by downloading applications on our smartphones, we can do things we never even imagined some ten

Ready to learn Big Data? Browse Big Data Training and Certification Courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. Digital Transformation can mean a lot of different things to different people. But for everyone it means dealing with more data than ever before. Industry 4.0, cloud, robotics, “big data,” artificial intelligence,

Ready to learn Big Data? Browse Big Data Training and Certification Courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. Technology powers every aspect of an organization – from financial compliance and data processing down to manufacturing floor monitoring and supply chain security. Further adding complexity of the technology-enabled ecosystem is the

Ready to learn Data Science? Browse Data Science Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. BASIC DEFINITIONS A graph G is simply a way of encoding pairwise relationships among a set of objects: it consists of a collection V of nodes and a collection E of edges, each of

Ready to learn Data Science? Browse Data Science Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. It is no news today that Big Data and Analytics are transforming the way different industries function on a day to day basis. A few years ago, companies were using marketing automation for

Ready to learn Data Science? Browse Data Science Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. This curated list of mindset-changing books will help you become a better Data Scientist According to Drew Conway, the Data Science Unicorn is an expert in statistics, programming, and business. While much has been

Transfer Learning is the reuse of a pre-trained model on a new problem. It is currently very popular in the field of Deep Learning because it enables you to train Deep Neural Networks with comparatively little data. This is very useful since most real-world problems typically do not have millions of labeled data points to train such complex models. This blog post is intended to give you an overview of what Transfer Learning is, how it works, why you should use it and when you can use it. 

For medium-to-large-scale enterprises, distributed systems are unsustainable and centralized databases expensive to implement. Gradually transitioning to a federated system is, therefore, an efficient solution. Downsizing the satellite databases while building a central database allows large firms to eliminate unnecessary personnel, equipment, and facilities gradually and strategically, increasing the odds of success. Even if it takes years to complete, a federated database created carefully and managed meticulously will pay in dividends, in part by helping enterprises improve their Data Management Maturity.

Ready to learn Data Science? Browse courses like Data Science Training and Certification developed by industry thought leaders and Experfy in Harvard Innovation Lab. Data scientists are in high demand, taking the number 1 spot in Glassdoor’s Best Jobs in America list in 2016 and 2017, with 4,84 position available and boasting a median base salary of $110,000. DevOps

Notebooks are being used as dashboards and also as artifacts in the data engineering and transformation process. Data visualization in R has grown nearly as robust and interactive as data visualization in BI tools or custom applications. People are growing more comfortable with stylized data visualization. These factors all contribute to what I think will define the third wave of data visualization where modes like notebooks, dashboards, and long-form storytelling converge, as will the tools to create them and the literacy of the audiences they are made for.