Firestore Data Model: An Easy Guide April 12th, 2022 By Vishal Agrawal in Data Strategy Firestore is a NoSQL, document-oriented database modeling and relationship builder, which means no tables or rows exist, unlike SQL databases. So, you store data in documents that are later organized…
What is AWS SQS (Simple Queue Service)?: 5 Comprehensive Aspects April 11th, 2022 By Abhinav Chola in Data Strategy Modern developers create complex applications that require a communication setup for exchanging messages among their components. Moreover, even a slight change in the message sequence can render the application useless…
RabbitMQ Exchange Types: How messages are sent and received April 11th, 2022 By Syeda Famita Amber in Data Strategy RabbitMQ is a lightweight, open-source, and easy-to-deploy message broker that enables services and applications to communicate with each other. It supports multiple messaging protocols like AMQP (Advanced Message Queuing Protocol),…
Understanding Predictive Forecasting Simplified 101 April 11th, 2022 By Aditya Jadon in Data Strategy Anyone running a business wants to predict its future. Though it is not possible exactly to some extent, you can get an estimation because business comes with uncertainty and risks…
Working with Java REST APIs: 3 Comprehensive Aspects April 11th, 2022 By Abhinav Chola in Data Strategy, Rest API This article will introduce you to the Java Programming Language and REST APIs along with their key features. It will also explain the structure and working of REST API calls.…
AWS SQS SendMessage Command 101: Syntax, Easy Steps & Examples April 11th, 2022 By Osheen Jain in Data Strategy In modern Cloud Architecture, systems decouple applications into independent, smaller building blocks that are easier to develop, maintain, and deploy. Message queue provides coordination and communication between these distributed applications…
Data Ingestion Google Cloud Simplified 101 April 11th, 2022 By Manisha Jena in Data Ingestion, Data Strategy Creating Cloud-based Data Ingestion pipelines that replicate data from multiple sources into your cloud data warehouse can be a huge project that demands a lot of manpower. Such a massive…
AWS Lambda Docker Image: An Easy Guide April 8th, 2022 By Yash Arora in AWS, Data Integration With high scalability, fault tolerance infrastructure, and pay-per-value services pricing model, AWS Lambda, with its latest support — AWS Lambda Docker Image — now caters to a broader audience of developers, helping…
Methods to Document Data in Data Mining Simplified 101 April 8th, 2022 By Raj Verma in Data Strategy In this age of Information Economy, data is generated from every digital computing device, handheld phone, workstation, server, and so on. Organizations are storing, processing, and analyzing data more than…
RDS Oracle PostgreSQL Integration: 2 Easy Methods April 8th, 2022 By Hitesh Jethva in Data Integration, PostgreSQL Easily move your data from RDS Oracle PostgreSQL to enhance your analytics capabilities. With Hevo’s intuitive pipeline setup, data flows in real-time—check out our 1-minute demo below to see the…
Entity Data Model Designer: a Comprehensive Guide 101 April 8th, 2022 By Harshitha Balasankula in Data Strategy While there are many Data Modeling tools available, there is a free one in Visual Studio. It is called the Entity Data Model Designer. The Entity Framework Models can be…
Salesforce Batch Jobs 101: Configuring Salesforce Apex Jobs Simplified April 8th, 2022 By Roxana Raducanu in Data Strategy, Sales Operations Salesforce is one of the most popular customer relationship management tools that allow you to streamline Customer Interactions, Marketing Operations, and Overall Sales. According to a report, over 150,000 websites…
What are Azure Data Factory Triggers?[+Examples and Types] April 8th, 2022 By Ishwarya M in Data Strategy Azure Data Factory is one of the most popular Cloud-based Data Integration Services that allows you to create, manage, and schedule Data Pipelines or Workflows. It has a rich set…
What is Data Ingestion? A Complete Guide April 7th, 2022 By Amit Phaujdar in Data Ingestion, Data Strategy Organizations depend heavily on data for predicting trends, planning for future requirements, making business decisions, understanding consumers, and predicting the market. However, to execute these tasks, it is necessary to…
Azure SQL to SQL Server: 2 Easy Methods April 7th, 2022 By Roxana Raducanu in Data Integration, SQL Server Azure SQL Database is a Relational Database service that is always up to date and designed for modern Cloud applications. It is part of the Azure SQL family. Most Database…
Understanding Google Cloud SQL High Availability: Simplified 101 April 7th, 2022 By Shravani Kharat in Database Management System, MySQL Building a fault-tolerant, highly scalable cloud-based application has become increasingly important as the demand for cloud-based applications is growing rapidly. However, robust applications are often supported by several components/software. This…
What is Streaming Kafka Data Pipeline and How to Build It? April 7th, 2022 By Aditya Jadon in Data Engineering, Data Pipeline To stay ahead of their competitors, organizations use data-driven approaches to run their business operations efficiently. Applications or websites with lagging services can hinder business growth. To deliver high performance,…
What is Data Validation – Simplified 101 April 7th, 2022 By Manisha Jena in Data Strategy Data integrity becomes increasingly more important as more B2B firms use data-driven techniques to enhance revenue and improve operational efficiencies. The inability to trust business data gathered from a variety…
How to Create and Structure Data Science Workflow April 6th, 2022 By Samuel Salimon in Data Strategy In this article,You will also gain a holistic understanding of how to structure a Data Science Workflow and what should be kept in mind while following the different steps in…
Descriptive and Predictive Data Mining Comparison: 6 Critical Differences April 6th, 2022 By Harshitha Balasankula in Data Strategy The main goal of Data Mining is to find valid, potentially useful, and easily understandable correlations and patterns in existing data. Data Mining can achieve this goal by modeling it…