Covering Data Science, Business Intelligence, Technology Industry News Updates and Trends
Introduction Business leadership should not get involved with making technical decisions, or managing technical teams because when they do, they destroy the engineering side of a tech company. New industry…
Hiring and retention insights for achieving continuous growth in software industry.
Introduction It is very important to have a local development and testing environment for developing data pipeline. Having a local development environment means you can try things and innovate with…
Chatbots are increasingly being developed and are highly successful in the financial domain, especially banking, insurance, and e-commerce sector.
Chatbot are growing importance since they enable an easy interactive interface between humans and computers leading to countless business and social use cases. It is an active research area and…
Data Lakes are the foundation for building AI driven solutions that many organizations need. There is much more information in audios, videos, images and social media chatter that can drive…
This tutorial will cover how to install PostGIS on Ubuntu 18.04 Linux for Greenplum 6 clustered setup. PostGIS is an open source PostgreSQL database extension for creating Geographic objects on…
Anaconda distribution of Python is the best option for problem solvers who want to use Python. Anaconda is free (although the download is large which can take time) and can…
This tutorial shares basic steps for setting up a python application from scratch using Anaconda and Visual Studio Code.
Windows functions are an important tool for data analysis. In this tutorial, we go through windows functions in SQL and provide examples for their use in Greenplum.
Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly. With Docker, you…
Quick reference for essential Git commands.
This article focuses on developing understanding and hands-on skills for carrying out exploratory data analysis over any given dataset.
Introduction To be successful as data analysts you need to learn fundamental data analysis techniques, and data-oriented programming languages, and have a strong background in math. Here are the most…
Are looking for a tool to visualize, explore and analyze data that can be modified and adapted to organizational architecture while it does not cost a fortune? Apache Superset is…
Industry Business Use Case Marketing and Sales 1). Increasing Sales Using Market Basket Analysis 2). Understanding Customer Sentiments 3). Personalized Content Recommendation 4). Customer Segmentation 5). Fraud Analysis and Prediction…
NLP Analysis Pipeline in Opener Library NLP pipeline implemented in Opener library has the following steps: Language Identifier Tokenizer Stemming Part of Speech(POS) Tagger Named Entity Recognition(NER) Named Entity Linking…
What is Feature Engineering ? Feature engineering is an important step in the data science pipeline. One of the most important questions facing data scientists is how to choose which…
We often hear that data analysts and data scientists should be proficient at listening to data and the art of storytelling with data, but what does that mean? We can…
In this code example, we will apply a convolutional neural networks(CNN) to textual data. More specifically, we will use the structure of CNNs to classify text. Unlike images, which are…