How to Choose a Data Serialization/Encoding Format? A Practical Guide for Engineers

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Data Encoding & Decoding. Image Source: Unsplash
Data Encoding & Decoding. Image Source: Unsplash 

In the world of software, we often work with different types of data like lists, tables, and more. These data structures are designed to be fast and efficient when our computer programs use them. However, sometimes we need to move this data out of our computer's memory, like when we want to save it to a file or send it over the internet. To do this, we have to change the data into a special format made up of 0s and 1s, which is quite different from data structures. This process is what we call encoding or serialization. 

Unlock Advanced Data Visualization: The Complete Guide to Installing and Using Apache Superset on Linux

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Data Visualization - Apache Superset Guide. Image Source: Unsplash

Data Visualization - Apache Superset Guide. Image Source: Unsplash 


Note: This article provides a comprehensive guide on deploying and using Apache Superset on a Linux server. It covers the installation and configuration process, as well as the benefits and features of Superset. While the primary focus is on Superset, we will also explore the broader concepts of business intelligence, data analytics, and visualization.

How to perform join operation in BigQuery? Exploring BigQuery Join Operations: Broadcast and Hashing Joins & Nested and Repeated Structures.

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BigQuery - SQL Joins
BigQuery - SQL Joins (Photo by Resource Database on Unsplash) 


SQL joins are used to combine columns from multiple tables to get desired result set. In a typical Relational model we use normalized tables, each table represents an entity (example: employee, department, etc) and its relationships and when we need to get data from more than one tables, for example employee name and employee department, we use joins to combine employee name column from employee table, department name column from department table based on employee number key column, which is available on both the tables.

GCP Cloud Pub/Sub Replay: Seeking to timestamp & Seeking to snapshots

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Google Cloud Pub/Sub Replay (Pixabay)
Google Cloud Pub/Sub Replay (Pixabay) 


Let's assume, you have data pipeline deployed on Google Cloud Platform, events are published to Cloud Pub/Sub topic from publisher client, and subscribed by a data processing application, which reads data from the Cloud Pub/Sub subscription, process it and write it to BigQuery table.

[Solved] Access is denied - Check credentials and try again - Microsoft Graph - Calendar API

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Access is denied - Check credentials and try again - Microsoft Graph - Calendar API
Microsoft Graph (Source: microsoft.com)


When sending API request to Microsoft Graph API, it responds with access denied error. You might have followed the documentation and added the correct permission and granted admin consent for the same, but it still produces the same error. Lets check the solution for this issue in this short article.

Streaming Analytics in Google Cloud Platform (GCP) - Building Data Pipeline with Apache Beam

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Building Apache Beam Data Pipeline
Building Apache Beam Data Pipeline (Source: Pixabay) 


In introduction article of this series Streaming Analytics in Google Cloud Platform (GCP) - Introduction, we have seen the basics of streaming analytics, its importance and example uses cases, and short introduction about the Google Cloud Services, we will be using to build Streaming Analytics system in Google Cloud Platform.

Streaming Analytics in Google Cloud Platform (GCP) - Setting Up The Environment

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Streaming Analytics in GCP
Streaming Analytics in GCP (Source: Pixabay) 


Hello everyone, in the previous article Streaming Analytics in Google Cloud Platform - Introduction, we have covered what is streaming analytics, what services we are going to use and a quick introduction to each service. In this part of the series, we will begin the installation of SDKs, and libraries and set up our environment.


Streaming Analytics in Google Cloud Platform (GCP) - Introduction

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Streaming Analytics in Google Cloud Platform
Streaming Analytics in Google Cloud Platform (image source - pixabay) 

From data-to-decision in real-time 

Welcome to our new series on building a streaming analytics system in the Google Cloud Platform!. Let's begin with a quick introduction. Streaming analytics is the process of analysing data in real-time as it is received. Streaming analytics enables an organisation to gain insights and make decisions based on the most up-to-date data, in real time. This is crucial for business as it allows organisations to respond to changes and opportunities in a timely manner.

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