fabiochiu/medium-articles huggingface dataset:
Turning Airflow into a full self service Data Platform
By: Daniel R Carletti
Tags: Data Engineering, Analytics, Data Platform, Airflow, Automation

Apache Airflow logo

Apache Airflow has become one of the most widely used data engineering tool on the market. That’s no coincidence, as it is an awesome tool. Easy to install, scalable, compatible with pretty much everything in the market and very easy to use.

Even though Airflow is easy to get the hang of, it is yet another tool to learn. For teams that will not work with it on a daily basis, it is not so trivial. That could lead to an overloaded data engineering team, working overtime to automate jobs that could easily be handled automatically.

For example: a Data Scientist has a Spark code that retrains a model, and needs it to be executed weekly. So, on top of building that, you are going to make this person create an Airflow DAG to do that? Come on, that’s not cool. Let’s automate that process!

That’s where your Data Platform engineer comes in. And here’s the cool thing about Airflow: DAG definitions are done in code, not a fancy UI interface. That means you can define many DAGs in a loop, using a config file for their intricacies. Something like:
Running Airflow with Docker on EC2 + CI/CD with GitLab
By: Ammar Chalifah
Tags: Docker, Data Pipeline, Ec2, Airflow, Gitlab

I’ve been learning data science for a year, yet until several weeks ago I still found myself completely clueless on the engineering side. Data analysis and artificial intelligence are stuff on the top of the pyramid, which requires strong data pipeline foundation. With this post, I will share my lessons learned while trying to built a simple data pipeline using Airflow, an open source orchestration tool. This orchestrator is deployed on top of Amazon EC2, utilizing GitLab’s CI/CD to ease up development process. Okay, one by one, let’s talk about definition of each terms.

Airflow

Based on its website, Airflow is a “platform created by the community to programmatically author, schedule and monitor workflows.” Airflow usually used by Data Engineers to orchestrating workflows and pipelines. Let’s say a Data Engineer need to move data from a source to another destination four times a day (e.g. to keep the freshness of the data). Instead of doing that task manually, they can automate the script to run on a particular schedule using Airflow. Airflow can also be used to manage dependencies, monitor workflow executions, and visualize workflows.

Airflow needs to be installed in a machine. Instead of using local computer, it is better to install it in a cloud-based host to improve reliability.

Amazon EC2

Amazon EC2 (stands for Elastic Compute Cloud) is a rented cloud-based computers offered by Amazon Web Services. EC2 will serve as the host, which Airflow will be deployed on. EC2 is just a computer, like our local laptop/computer, but the machine will be up 99% of the time and managed by AWS team. We can ‘tunnel’ our way inside the command line interface of EC2’s machine by using SSH. Later on, we will learn how we can use SSH and git to deploy codes from a remote repository to EC2.

Docker

Airflow won’t be installed directly on EC2 local machine, but installed inside a Docker container. Docker is a set of platform that creates virtual OS called containers. We use Docker to reduce setups, as all setups will be managed by the maintainer of the Docker images (in this case, Airflow contributors). A Docker image contains application code, libraries, tools, dependencies and other files needed to make an application run. We will pull an image from Docker image registry, build it, start the container, and run Airflow inside.

GitLab

GitLab will be used as our repository and DevOps lifecycle tool. There are practically countless way we can utilize CI/CD in GitLab, but for the sake of simplicity we will only use the ‘CD’ part. Every time user merge any branch into the main branch, the deployment script will be triggered. Deployment pipeline consists of SSH tunneling into our EC2, pulling main branch from GitLab repository into EC2, write several variables to a file, and rebuild + restart the Docker container.

Before diving into the details, check this repository, which contains the complete codebase and summary of the steps that we will take to successfully create a continuous deployment pipeline of Airflow. Okay, let’s start!
Setting up Apache Airflow 2 with Docker
By: Danilo Trombino
Tags: Data Engineering, Docker, Airflow, Cloud Computing, Etl

Introduction

Apache Airflow 2 is finally out. Among the new features announced (a brand new scheduler, stable REST APIs and much more) a production-ready Dockerfile has been released. This allows developers to deploy Airflow using modern cloud technologies rather than installing it on bare metal.

In this article we will take a look at how to create a local environment using VirtualBox and Vagrant, install Docker and deploy a production-ready Airflow container. Let’s start!

Local Environment

In this section we will see how to create a virtual machine, install docker and configure a shared folder to easily access local files in the guest machine. Feel free to skip this part if you don’t want to use a VM for your experiments.

Configure a virtual machine

Assuming you have already installed VirtualBox and Vagrant on your local machine, this is the manifest (Vagrantfile) that represents the virtual machine we want to build:

Vagrantfile

This manifest specifies how “airflow-vm” (hostname) must looks like:

based on ubuntu/xenial64 image

4GB of RAM

uses IP 192.168.1.200

mounts shared folder (must be created in the same path as Vagrantfile) under /opt/airflow

Open a new terminal window, move to the Vagrantfile path and simply type:

vagrant up

vagrant ssh

Install Docker

Now it’s time to install Docker on this brand new VM. We will use the official docker-install script by typing:

curl -fsSL https://get.docker.com -o get-docker.sh\

sh get-docker.sh\

If everything went ok we should be able to run the following command:

sudo docker run hello-world

Airflow 2 on Docker container

In this section we will start from the official Docker image (v2.0 stable) adding a thin layer on top of it to automatically create an admin account and to easily configure an external Postgres database in order to enable parallelism through Local Executor.

The approach

Let’s start from the end (yes, Nolan changed my mind with Tenet). Our goal is to create a stack composed by Airflow 2 (web server and scheduler can be deployed separately, but for this article an all-in-one solution might be more appropriate) and a Postgres database. We will use the following docker-compose file:

docker-compose.yaml

Here we are defining 2 services: postgres (our db) and server (airflow).

Let’s break it down!
A Beginner’s Guide to Apache Airflow — Part 3: Intro and Setup
By: Jessica Le
Tags: Dbt, Data Engineering, Data, Google Big Query, Airflow

2.2 The Noodle Analogy

There are 3 main key concepts we should be looking at in this early stage — docker image , docker-container and docker compose .

Suppose you are an instant noodle lover who loves to make your own recipe, so you create the awesome recipe with unique ingredients and method on how to make an awesome bowl of noodle. So what do u do next? You pack it nicely easily readable format, which is called noodle recipe — This is similar to docker image . It contains your specific instructions in the instant noodle cup.

After packing, you send to your 24-hours supermarket where anyone can enjoy your awesome noodle bowl for free. This 24-hours supermarket is docker registry . Assuming your shiba inu (I love dogs) likes to eat noodle. He can go to the supermarket and get one package of your awesome noodle. After he gets home, he just needs to follow the instructions which is similar running the command docker run . After following the instructions, finally he has an awesome noodle — This is similar to having a docker container . And this docker container will be running some applications.
Running Containers on Cloud Composer (the right way)
By: Sayle Matthews
Tags: Featured, Containers, Google Cloud Platform, Airflow, Google Kubernetes Engine

Edit: This article is written specifically for Airflow 1.X running on Cloud Composer. Since writing Google has released Airflow 2.X in preview mode on Composer and I have written this article which updates the code used in this article to Airflow 2.X. I recommend going through this article first then reading the other.

Here at DoiT International, a very common support ticket we have gotten lately is how to run containers on Cloud Composer (managed Airflow) effectively.

Since Cloud Composer runs on top of a Google Kubernetes Engine (GKE) cluster, this allows for massive scalability and working around the limitations of the other managed Airflow services out there.

While doing a quick search shows the KubernetesPodOperator as being the solution, there are some “gotchas” that come along with that especially when running it on Cloud Composer.

This article clears that up and gets you running your DAGs (Directed Acrylic Graph) with containers in an efficient manner.

The Crux of KubernetesPodOperator on Composer

The KubernetesPodOperator class is the method of running containers on Cloud Composer, but it has one major flaw: it runs all containers on the same nodes as the DAGs running on Airflow. This means it’s competing with them for resources.

This may not sound so bad, but there are scenarios that could cause problems for you. For example, one of our customers started getting exceptions on running containers inside of a DAG because their other DAGs were using too much memory.

The underlying GKE cluster was unable to schedule additional DAGs and tasks so Airflow just started throwing a timeout exception when trying to run any KubernetesPodOperator task. Due to this, their mission-critical DAG that contained a container was unable to run. If this had been a DAG that calculated payroll or bonuses for the year-end then it definitely would’ve been a major problem with serious implications.

This brings us to the solution to this particular issue, but first a few small explanations on how GKE works. If you are familiar with GKE then feel free to skip the next two sections and get straight to the solution.
Spark Joins Tuning Part-1(Sort-Merge vs Broadcast)
By: Sivaprasad Mandapati
Tags: Big Data Analytics, Data Engineering, Big Data, Data Science, Spark

Parallelization is Spark’s bread and butter. The back bone of Spark architecture is Data should be split into pieces(Partitions) and allocate each piece to an executor in cluster, So multiple executors can work on different pieces of data in parallel .

A single row level operations like Mapping, Filtering makes Spark’s job easy , but when it comes to multi-row level operation like joining, grouping , data must be shuffled first before doing actual operation . Shuffling is very costly operation . It hits all your resources in the cluster

Shuffling : All the nodes and executors should exchange the data across the network and re-arrange partitions in such a way that each node/executor should receive a specific key data.

In this article, I would like to discuss most common spark join types and their use cases with an example.

Sort Merge Broadcast

Let’s first understand on high-level how spark performs above join methods in the backend and then explore with an example.

Sort-Merge :

By default , Spark uses this method while joining data frames. It’s two step process. First all executors should exchange data across network to sort and re-allocate sorted partitions. At the end of this stage , Each executor should have same key valued data on both data frame partitions so that executor can do merge operation. Marge is very quick thing.

Let’s examine this sort merge join with an example . Two data frames A and B have four key columns (1,2,3,4) and let’s say we have 2 node cluster

Sort Phase : As you can see, both A and B are sorted by Join key i.e. Key column and sorted data is split into 2 partitions . Each partition should have specific key data. There should not be any overlapping of Keys between partitions which is hole idea of shuffling

Assign sorted partitions to executors

Merge Phase : Merging sorted data by keys is very simple and quickest operation.

Broad Cast Join :

We have observed , Sort-Merge join requires full shuffling of both data sets via network which is heavy task for Spark . What if we can eliminate shuffling . How can we do it ? replicate the whole small table to all executors .

Sort-Merge vs Broadcast :

I have an example data set Sales Fact table and Products Dimension table . Sales Fact Table is very big in size and Products is quite simple .

Verdict : broadcast join is 4 times faster if one of the table is small and enough to fit in memory .

I love any law or theory with examples and proofs .Please find below code snippets and results
Big Data Analyst Training in Mohali
By: Naman Srivastava
Tags: Big Data Analytics, Big Data, Artificial Intelligence, Python

Big Data Analyst Training in Mohali

Introduction Hadoop Fundamentals

The Motivation for Hadoop

Hadoop Overview

Data Storage: HDFS

Distributed Data Processing: YARN, MapReduce, and Spark

Data Processing and Analysis: Pig, Hive, and Impala

Database Integration: Sqoop

Other Hadoop Data Tools

Exercise Scenarios

Introduction to Pig

What is Pig?

Pig’s Features

Pig Use Cases

Interacting with Pig

Basic Data Analysis with Pig

Pig Latin Syntax

Loading Data

Simple Data Types

Field Definitions

Data Output

Viewing the Schema

Filtering and Sorting Data

Commonly Used Functions

Processing Complex Data with Pig

Storage Formats

Complex/Nested Data Types

Grouping

Built-In Functions for Complex Data

Iterating Grouped Data

Multi-Dataset Operations with Pig

Techniques for Combining Datasets

Joining Datasets in Pig

Set Operations

Splitting Datasets

Pig Troubleshooting and Optimization

Troubleshooting Pig

Logging

Using Hadoop’s Web UI

Data Sampling and Debugging

Performance Overview

Understanding the Execution Plan

Tips for Improving the Performance of Pig Jobs

Introduction to Hive and Impala

What is Hive?

What is Impala?

Why Use Hive and Impala?

Schema and Data Storage

Comparing Hive and Impala to Traditional Databases

Use Cases

Querying with Hive and Impala

Databases and Tables

Basic Hive and Impala Query Language Syntax

Data Types

Using Hue to Execute Queries

Using Beeline (Hive’s Shell)

Using the Impala Shell

Hive and Impala Data Management

Data Storage

Creating Databases and Tables

Loading Data

Altering Databases and Tables

Simplifying Queries with Views

Storing Query Results

Data Storage and Performance

Partitioning Tables

Loading Data into Partitioned Tables

When to Use Partitioning

Choosing a File Format

Using Avro and Parquet File Formats Course details:

Relational Data Analysis with Hive and Impala

Joining Datasets

Common Built-In Functions

Aggregation and Windowing

Complex Data with Hive and Impala

Complex Data with Hive

Complex Data with Impala

Analyzing Text with Hive and Impala

Using Regular Expressions with Hive and Impala

Processing Text Data with SerDes in Hive

Sentiment Analysis and n-grams

Hive Optimization

Understanding Query Performance

Bucketing

Indexing Data

Hive on Spark Impala Optimization

How Impala Executes Queries

Improving Impala Performance

Extending Hive and Impala

Custom SerDes and File Formats in Hive

Data Transformation with Custom Scripts in Hive

User-Defined Functions

Parameterized Queries

Choosing the Best Tool for the Job

Comparing Pig, Hive, Impala, and Relational Databases

Which to Choose?

Being one of the top Big Data Training Company in Mohali and a Certified Microsoft Authorized Education Partner, Cisco Partners, Intel Technology Provider, Google Certified Professionals & IBM Certified. Itronix Solutions deals with 100% Job Placements for Eligible Students after successful completion of the course.
What is Business Analytics?
By: Step Dorogov
Tags: Big Data Analytics, Big Data, Analytics, Business Analysis, Business Development

Analytics describes and, as a result, takes measures to change various internal parameters. They add value to the company by identifying needs and justifying decisions. Today, any company, regardless of its size, understands that business analysis is necessary in order to withstand the competition and develop further.

Even if you have a small grocery store, without realizing it yourself, you perform simple, but still business analytics: you calculate how much to buy each of the goods, why exactly this and exactly how much, agree with suppliers and a logistics company.

Analysis tasks

The analysis involves the study of reports and data by dividing them into separate component parts. And the business itself is also a system consisting of several interconnected parts that interact, and the efficiency of the business as a whole depends on the effectiveness of their interaction.

Each company sets itself tasks individually, based on generally accepted goals: for some, it is important to reduce the cost of a certain project, for others — to receive additional investments, someone wants to complete the project on time, increase profits, etc.

Business analytics goals

Business analysis is performed to achieve the following results:

Reduced costs

Finding a solution to the problem

Improving project efficiency

Completion of projects on time

Documenting all requirements

Our solutions

The business analysis must be fast, accurate, and affordable. Of course, large amounts of data amassed by companies make business analysis difficult. And here big data comes to the rescue for analyzing big data. We implement software solutions for automated data collection and analysis.

Our solutions allow you to process:

Any amount of data

From any source

At high speed

And as a result, present the processed data in the form of beautiful, convenient, understandable and interactive graphs. With the help of such a solution, you can see the picture of the efficiency of the business as a whole and immediately move to a lower level in seconds — sales by category or the employment of employees.

Any business owner can independently work with such solutions — this does not require special knowledge. And most importantly, on the basis of this information, one can and should draw conclusions, predict and make fateful decisions. Thanks to the software, you do not need to wait days, weeks or months for specialists to generate department reports for you, everything is calculated in seconds.

Such automated systems can be used in any area:

Online Marketing

Sales

E-commerce

Logistics

HR department

Accounting and finance department, etc.

It is as easy as shelling pears to scale up a business in the market, have complete control over every detail, or integrate IoT technologies into your system. CimpleO brings you high-quality IoT software tailored to your needs. We do not resell someone else’s. We create unique designs with individual functionality not available in mass-market products.
Big Data Analytics
Tags: Big Data Analytics, Bigdatacourse, Big Data Training

What is Big Data Analytics and Why It is Important?

By SimplilearnLast updated on Mar 28, 202118435

Big Data is today, the hottest buzzword around, and with the amount of data being generated every minute by consumers, or/and businesses worldwide, there is huge value to be found in Big Data analytics.

What is Big Data Analytics?

Big Data analytics is a process used to extract meaningful insights, such as hidden patterns, unknown correlations, market trends, and customer preferences. Big Data analytics provides various advantages — it can be used for better decision making, preventing fraudulent activities, among other things.

Why Big Data Analytics?

Big Data analytics is fueling everything we do online — in every industry.

Take the music streaming platform Spotify for example. The company has nearly 96 million users that generate a tremendous amount of data every day. Through this information, the cloud-based platform automatically generates suggested songs — through a smart recommendation engine — based on likes, shares, search history, and more. What enables this is the techniques, tools, and frameworks that are a result of Big Data analytics.

If you are a Spotify user, then you must have come across the top recommendation section, which is based on your likes, past history, and other things. Utilizing a recommendation engine that leverages data filtering tools that collect data and then filter it using algorithms works. This is what Spotify does.

But, let’s get back to the basics first.

Big Data is a massive amount of data sets that cannot be stored, processed, or analyzed using traditional tools.

Today, there are millions of data sources that generate data at a very rapid rate. These data sources are present across the world. Some of the largest sources of data are social media platforms and networks. Let’s use Facebook as an example — it generates more than 500 terabytes of data every day. This data includes pictures, videos, messages, and more.

Data also exists in different formats, like structured data, semi-structured data, and unstructured data. For example, in a regular Excel sheet, data is classified as structured data — with a definite format. In contrast, emails fall under semi-structured, and your pictures and videos fall under unstructured data. All this data combined makes up Big Data.

But, Big Data in its raw form is of no use. So, now let us understand Big Data Analytics.
BigData Analytics
By: Naveen Kumar
Tags: Big Data Analytics, Bigdatacourse, Big Data Training, Big Data

Big data analytics applications often include data from both internal systems and external sources, such as weather data or demographic data on consumers compiled by third-party information services providers. In addition, streaming analytics applications are becoming common in big data environments as users look to perform real-time analytics on data fed into Hadoop systems through stream processing engines, such as Spark, Flink and Storm.

Early big data systems were mostly deployed on premises, particularly in large organizations that collected, organized and analyzed massive amounts of data. But cloud platform vendors, such as Amazon Web Services (AWS) and Microsoft, have made it easier to set up and manage Hadoop clusters in the cloud. The same goes for Hadoop suppliers such as Cloudera-Hortonworks, which supports the distribution of the big data framework on the AWS and Microsoft Azure clouds. Users can now spin up clusters in the cloud, run them for as long as they need and then take them offline with usage-based pricing that doesn’t require ongoing software licenses.

Big data has become increasingly beneficial in supply chain analytics. Big supply chain analytics utilizes big data and quantitative methods to enhance decision-making processes across the supply chain. Specifically, big supply chain analytics expands data sets for increased analysis that goes beyond the traditional internal data found on enterprise resource planning (ERP) and supply chain management (SCM) systems. Also, big supply chain analytics implements highly effective statistical methods on new and existing data sources.

Read more for BigData Analytics
MongoDb connector-Spark with Scala
By: Satabdi Ray
Tags: Big Data Analytics, Spark, Scala, Mongodb

If there is a requirement to add MongoDb connector to a Spark application written in scala, then here you can refer below code snippet(Test.scala) which will help you to read from MongoDb and writing a Dataframe to this locally provided you have been given with connection details.

Mongo DB details:

Database: [database name]

user: [user name]

pass: [password]

Connecction string: mongodb://username:password@ec2-xx-xx-xxx- xxx.xx-xx-x.compute.amazonaws.com:27017/

First you have to create a sample table in MongoDb and import data to it from any file system(say csv). Next you have to read this table as a Dataframe to your Spark. After reading you can do some query onto it and create a new table where you can write the results of the query as a dataframe there in MongoDb.

4. And in build.sbt, add the below library.(it depends on Scala version used in your application)

libraryDependencies += "org.mongodb.spark" % "mongo-spark-connector_2.11" % "2.4.1"

5. Create a test.scala file, run it locally using the above and verify if you are able to connect to MongoDb and do read/write operations.

This is written to do a quick connection test from your local environement to MongoDb. Hope this helps!
Data Breach of the Week — Facebook
Tags: Messaging, Decentralization, Privacy, Data Breach

Facebook has been a major part of our lives since 2004. Since its inception people have been sharing their photos, opinions and location, while the platform gathered more and more information about its users.

When you look at all of the issues that Facebook has had over its time in our lives, the stories are overwhelming.

Let’s break down the main ones

Cambridge-Analytica Scandal

It was discovered that in 2016, a political firm hired by the Trump campaign acquired access to private data on millions of Facebook users. Cambridge-Analytica gained access to more that 50 million Facebook Users private information. The firm then used the information and was able to offer tools that could identify the personalities of American voters and influence their behavior. They would target specific ads at users based on what the users “liked.” Users were asked to take a personality survey and download an app, which scraped private information from their profiles and those of their friends. This activity has since been banned by Facebook.

Facebook does not consider this to be a data breach because it allows researchers to gather user’s information for academic purposes.

Data Breaches

There are too many data breaches to name of them all. As recently as December 2019, there was news of a data leak that exposed over 419 million users phone numbers. The phone numbers were linked to Facebook ID’s.

Current Privacy Issues

Even now, Facebook is using a tool called “Off-Facebook Activity,” that tracks your app and website history. This tool shows exactly how much Facebook is watching your every move. The tracker will show 180 days’ worth of data that Facebook collects.

There is a way of clearing your history and turning off this tool.

Open your app and click the menu icon in the bottom bar (the icon on the far right) Open the Setting & Privacy menu and Select Settings Scroll down to “Your Facebook Information” and select “Off-Facebook Activity” Click on “Clear History” to clear your current Off-Facebook Activity Click on “More Options” and select “Manage Future Activity” Click on “Manage Future Activity” Toggle the “Future Off-Facebook Activity” off

With little trust left in Facebook, the question isn’t “what else can Facebook do to secure it’s platform”, it’s “why do we as users keep on coming back and using their platform even though they have wronged us so many times?”

It’s time for ALLY.

ALLY is the new, decentralized, and private place to foster communities and connect with people globally, without fear of third-party entities and government censorship. ALLY is a safe haven where people around the world can practice free speech without retribution and can share data openly without that information being stored, hacked and manipulated. ALLY is built to secure users’ information and is the communication and crypto hub for the entire world.

Be sure to follow us on Twitter and Telegram to stay up to date on the latest ALLY news!
Best Messaging Apps For Your Phone
By: Scaramanga Smart
Tags: Mobile Apps, Apps, Messaging, Messaging Apps

In this era of technological advancement, people are increasingly using smartphones for constant and instant communication with their family, friends, and work colleagues. The use of smart messaging applications like Whatsapp, Telegram, LINE, Smart Callee, etc to stay connected is becoming increasingly popular.

With the evolution of smart messaging, the traditional short messaging service (SMS) and multimedia messaging service (MMS) is now passé. Messaging apps are now being designed to provide rich services like free text messaging, voice and video calling, group calling, photo and file sharing, location sharing, contact sharing, etc. with the added benefit of end-to-end encryption if you want to keep your conversations secret from anyone who isn’t involved.

The Android and iOS app stores are flooded so many messaging apps that choosing one might seem difficult and overwhelming. That’s why we’ve tested out a lot of different options and listed below some of the best messaging apps:

WhatsApp

One of the most downloaded and immensely popular messaging app, WhatsApp, designed to let you send text messages and make calls over the internet. It also lets you share location, contacts, documents, images, videos and voice messages. The best thing about WhatsApp is at it gives you an end-to-end chat encryption option if you want to keep your conversations secret from anyone.

Telegram

Telegram is a cloud-based messaging service that supports not only text messages but also audio calls and short audio messages. Unlike most messaging apps, Telegram allows you to edit and delete messages even after you’ve sent them. It also has a Secret Chat feature that lets you send timed messages that are automatically deleted once the specified time limit is reached.

Smart Callee

SMART Callee is an innovative messaging app that helps you summarize all your communications, over various channels and platforms, at one place and displays them on incoming and during calls. This way, SMART Callee helps you in optimal and efficient utilization of the call duration to have a productive conversation.

LINE

LINE is a smart messaging app that offers free user-to-user calls, video calls, and instant messaging. The app also offers allows subscribers to make paid calls to mobile devices and landlines domestically as well as internationally. It also facilitates the sharing of multimedia files like recorded voice files, video files & pictures and sending and receiving money among LINE app users.

Voxer

Voxer is a push-to-talk app that allows instant voice messaging. It also supports texting, photo messaging, and location sharing, in addition to providing military-grade security and encryption. Using this app, you can even make notes and reminders for yourself.

Was this article helpful? Do let us know in the comments below. In case you have any other questions for us, do comment below. Our experts will get back to you with the best possible solution.
What Message is Your Advertising Sending?
By: Manfred Bluemel, Zeitgeist Research
Tags: Advertising, Market Research, Messaging, Marketing, Advertising And Marketing

When was the last time you tested messages? Oops! Too late!

It’s probably happened to most of us. You’re watching television, and an advertisement comes on. “Whoa,” you think, “why are those people so close together? Why aren’t they wearing masks?” I call it PPSD (post-pandemic stress disorder).

Jokes aside, our perceptions about the way the world is and should work are changing rapidly. Remember, not long ago, nobody would have been distracted by an ad showing people without masks. So, if you’re running the same advertising now that you ran during the worst of the pandemic, you need to test it to make sure that your message is still getting communicated.

Three Key Methods of Testing Messages

Composite Score: When you’ve done your brainstorming and have generated a list of messages, how do you decide which one is the winner? We can quickly test your messages and give you a composite score that will help you select the best campaign message. Our composite score combines metrics across importance, memorability, brand fit, uniqueness, and more. Additionally, we analyze the competitive landscape to show you which competitors “own” what messages and identify unclaimed territory. This makes it easy to provide you with a unique positioning in the mind of your target audience and inform your creative strategy.

TURF Analysis: TURF (Total Unduplicated Reach and Frequency) analysis helps identify messages that have the greatest appeal and reach within the marketplace. Ideally, you would not run multiple ads against the same target audience. By understanding which combination of messages result in the widest appeal, you can develop a marketing campaign that gives you the broadest reach. As shown in the graphic below, reach can be maximized by offering message combinations that appeal to the largest population.

Conjoint Analysis: By analyzing each element of your advertising campaign, we can help you create the optimal vehicle for communicating your message. For example, we can figure out what image goes with what message and what headline goes with what tagline.

Message Testing is More Important than Ever

Now, more than ever, launching an advertising campaign can feel like a leap of faith. You need to message test your advertising because none of us can know what messages will motivate our target audience in these turbulent times. And that means you need to eliminate risk and quickly adjust to the changing marketplace. Zeitgeist Research’s experienced researchers are dedicated to delivering high-quality message test results quickly (sometimes in as little as a week), and affordably.

Contact Zeitgeist Research today. You will find you can’t afford NOT to test your messaging!
WECHAT MEET ITS CHALLENGER: BULLET MESSENGER
By: Wechat Mini Programmer
Tags: Web Development, Wechat, Messaging, Wechat Marketing, Wechat Mini Program

So finally there is a challenger for WeChat, China’s No 1 messaging app.

Yes, we are mentioning about Bullet Messenger which was launched on August 20, 2018. It’s powerful enough to give a strong shot at China’s truly monopolistic sector of messaging app, where Tencent’s designed app WeChat have control on 86 percent of the social media app users based out in China.

Bullet Messenger is emerging out to be one of the most downloaded free app on Apple’s App Store of China just within four days of its launch, as per the shared data of app analytics firm App Annie.

Its a startup of Kuairu having the backing of Smartisan which is a well-known Chinese smartphone maker, this newly designed messenger is forcing investors’ to turn heads. It locked its first funding 9 days back on 30th Aug,2018 at US$22 million. This announcement was done by Smartisan founder Luo Yonghao on Weibo.

Since its inception Over the years, WeChat turned into an all-in-one app. It allows users to complete a wide array of regular tasks starting from booking rides to make the payment of utility bills. But chances are pretty high that over time Bullet Messenger will develop more and turn out to be a sophisticated choice for China app users.
New Smart App: SwiftMQ to SwiftMQ Bridge
By: Andreas Müller
Tags: Integration, Swiftmq, Messaging System, Messaging

What is the SwiftMQ / SwiftMQ Bridge?

It is a Flow Director Smart App to create message bridges between queues and/or topics of the same or different SwiftMQ Routers. It creates a consumer on a source router, a producer on a target router, and transfers messages. The number of bridges you define is not limited. They run in parallel.

Configuration of bridges takes place through the app’s web interface by a simple setup wizard. Live dashboards display total and per-bridge throughputs.

When should I use the SwiftMQ / SwiftMQ Bridge?

If you need a bridge between queues and/or topics of the same or different HA or non-HA routers, on-premise or in the cloud.

If you don’t want to spend much time struggling with config files and deployments.

If you’re going to see your bridge traffic in live dashboards and have a single button to start/stop the bridges.

If you need to scale up by creating many bridges.

Can I get a Demo, please?

Of course. Book a 30-minute one-on-one Zoom demo here.

Where can I get the SwiftMQ / SwiftMQ Bridge?

It is a Smart App that runs on the free Flow Director platform, so you need to install it first. It takes you only 2 minutes. You don’t have to become familiar with the platform as we use it as runtime only. Then install the app in Flow Director, and you are done.

Check it out here.
Relationship Messaging
By: Diya Saini
Tags: Messaging, Relationships, Diya Saini, WhatsApp, Humor

Talk between the two guys on WhatsApp.

1st — Hey Chum

Have you reached

2nd — No, in the alley parking garage.

What about you?

1st — Totally fucked up

I got up late can’t make it

2nd — It’s okay, buddy.

I will ride back.

We will make it some other day.

1st — Thanks, pal.

Discussion between two women on WhatsApp.

1st — Hey, have you hit the mall.

2nd — Yes was an hour earlier to avoid traffic.

So what about you?

1st — Yes was so energized about this outing.

I’m in the restroom of the mall. I will catch you in a couple of minutes.

Dialogue between boyfriend and girlfriend.

Girl Friend — Hi dear, have you reached

Within 1sec

can you respond

Within 1sec

you are not picking up your call

Within 1sec

I’m sick of you not being on time.

Within 1sec

I’m splitting up with you.

Within 1sec

You don’t care a shit about me.

Someone slaps her on the shoulder. She turns and says, hi, you didn’t pick your call. Oh! I left in silence and forgot to take it back.

Tap Message Delete for Everybody.

Husband-Wife Conversation.

Wife — What time are you heading home?

It’s an hour later.

Husband — Will be late hanging out with friends.

Within one second

Wife — I have something important.

Husband — Fast, my friends are awaiting & calling me.

The wife sends in a video. The husband is left staring with an open mouth. Guys, I guess I should go right away. A guest invited himself un-called.

Husband, all happy and gay, reach the house to find the wife sleeping with cold food on the table.

Husband wobbles on waking his wife. She opposes him off, saying, I’m sleeping.

What was that pornography video of yours to entice me?

A new way to stimulate in seizing you home on time.
RabbitMQ Producer and Consumer Solution with Docker in .net Core
By: Ercan Erdoğan
Tags: Rabbitmq, Messaging, Microservices, Net Core, Message Broker

What is RabbitMQ?

“RabbitMQ is a message broker: it accepts and forwards messages. You can think about it as a post office: when you put the mail that you want posting in a post box, you can be sure that the letter carrier will eventually deliver the mail to your recipient. In this analogy, RabbitMQ is a post box, a post office, and a letter carrier.” (1)

It has developed by Erlang open source language.

Why we need to use RabbitMQ?

Now that you know what RabbitMQ is, the next question is: why should you use a queue instead of directly sending data from one microservice to the other one. There are a couple of reasons why using a queue instead of directly sending data is better (2)

Higher availability and better error handling

Better scalability

Share data with whoever wants/needs it

Better user experience due to asynchronous processing

As for usage areas, it will make our job much easier to perform tasks that do not need to be synchronized, such as sending mail, basket operations after adding an order on our e-commerce page, and export (excel, csv) data. (Generally “Message brokers”).

For example, when the user wants to export the data he sees on the screen to excel, when we do this via a queue, the user will not have to wait for the process to be completed. It will be able to continue its other work in the application while the export process continues asynchronously.

Which protocols does RabbitMQ support?

RabbitMQ speaks multiple protocols which are MQTT, STOMP), AMQP. (3)

AMQP (Advanced Message Queuing Protocol)

RabbitMQ was originally developed to support AMQP. As such this protocol is the “core” protocol supported by the broker.

STOMP (Simple (or Streaming) Text Orientated Messaging Protocol.)

STOMP is a text-based messaging protocol emphasising (protocol) simplicity. It defines little in the way of messaging semantics, but is easy to implement and very easy to implement partially (it’s the only protocol that can be used by hand over telnet). RabbitMQ supports STOMP (all current versions) via a plugin.

MQTT (The Standard for IoT Messaging)

MQTT is a binary protocol emphasising lightweight publish / subscribe messaging, targetted towards clients in constrained devices. It has well defined messaging semantics for publish / subscribe, but not for other messaging idioms.
Spiritual Practices for the Nonreligious
By: Ashley Richmond
Tags: Spirituality, Self Improvement, Mindfulness, Ritual, Routine

Spiritual Practices for the Nonreligious

Photo by Artem Kovalev on Unsplash

I’ve always liked the idea of religious disciplines and practices — reading scripture each morning, praying, attending church. However, I don’t really resonate with religion. I like the idea of nourishing the soul and having spiritual practices but have always struggled to find such practices or to follow someone, a philosophy, or a school of thought that’d provide these practices and daily guidance.

Over the past couple of years, I’ve actively sought out nonreligious spiritual practices to include in my daily routines. I’ve tried and experimented with many, and in this article, I’ll outline what I’ve tried that’s resonated with me — and how I implement these practices into my day.

I believe that practices in general are incredibly important, for everything from health to happiness. Practices are what provide guidance in our lives. I love Ryan Holiday’s article about practices and refer to it often.

“Practices are things you do regularly — perhaps daily, perhaps not — but in no particular order. They are things you return to, time and time again, to center yourself. To reset. To reconnect. To focus.” — Ryan Holiday

More and more, I’m realizing that life is about more than how much I’m benching at the gym or how much money I’m making with my business. I think when you’re young and your life is taking off, it’s so easy to get wrapped up in achievement and reaching milestones. I put so much value in eating well, exercising daily, and working hard every single day. I was brought up valuing these endeavors. I’m hugely ambitious.

But it’s true what they say — when we get to the end of life, how many reps we did, how much money we made, and how young we were when we bought a house won’t matter. We won’t even remember those things. We need to have more than just these shallow achievements. While ambition is still hugely important, especially at this point in our life, we must ensure we’re also engaging in regular meaningful practices.

Epictetus said, “It is quite impossible to unite happiness with a yearning for what we don’t have. Happiness has all that it wants.”

I think it’s through spiritual practices that we find happiness. It is these practices that return us to the now and reconnect us with the present moment. We can still yearn for more, of course. But we need to have something that anchors us. We need some sort of spiritual practice to remind us to be here now, to enjoy life now. To anchor us in meaning and to align us with our values.
Build a Routine: Small Habits Add Up to Permanent Improvements
By: Wil Henry
Tags: Self Improvement, Philosophy, Motivation, Routine, Growth

Small Habits Will Build a Routine

It can seem very difficult for you to build a routine into your daily life. Something you have to do consistently can be an extra weight on your already busy day-to-day life. The secret is that small habits will add up to routine if you work on them just a tiny bit at a time. You don’t have to be perfect tomorrow. You can start today with a single small improvement and you’re already doing better than you were.

Every Improvement Adds to the Whole System

Perhaps you’ve heard of goals and systems. People will tell you that goals are inferior to systems because goals tell you where you’re going and systems get you there. That’s true, but they work in unison. Set yourself small goals and big goals. The small goals create a path to follow. Then you create a system of tiny improvements in order to actually achieve those goals. It’s no more complicated than that.

Build a Routine of Good Habits to Succeed

Whatever kind of success you’re seeking, a good system built on reasonable goals and habits to achieve these goals will get you there. If you want financial success then you just have to build a routine to get there one step at a time. If you want physical success then you can start right now with some bodyweight workouts. It doesn’t matter where you are. If you want romantic success then you can write a love poem right now. It’ll be useful later.

What Habit Can You Improve Today?

Don’t put it off until tomorrow. Look at yourself right now and say one thing you could improve. Maybe you drink a sugary drink every day, as a treat. It’s your one treat. Well, it would be a small improvement toward your health to drink 6 a week instead of 7. It’s really that easy to improve yourself. Eventually, you’ll find that day off isn’t so difficult.

When the time comes you can cut another one out. It’ll be easier than the first. You’ll say, “Maybe I just want one a week.” and then you’ll realize you don’t even need that. Suddenly, you’re drinking unsweetened coffee and tea, and of course water. You’re building a routine that works for you.

You Don’t Need to Rush

If you’re finding it difficult to build the routine you want then just relax. It’s supposed to be one step at a time because a step is easy to take. If the step feels like you’re jumping off a cliff then you’re either very brave or very silly. Do what you can handle and don’t worry about the rest. Stress will only drive you back toward those sugary drinks.

Check out WilHenry.net for more content!
Siblings During Covid-19
By: Vartika Rawat
Tags: Lockdown, Siblings, Covid 19, Lifestyle, Routine

Photo by Kelly Sikkema on Unsplash

“Mumma! He is watching YouTube!” “No Mumma, he is the one who is playing games rather than attending class!” “No Mumma….”

And this is how we siblings start our day during the pandemic. Interesting right!? But you know what, this is not all! So today, we will talk about all the problems we siblings face while staying at home together, oh wait maybe I should say, stuck at home together..!!

Responsibilities

Okay, so someone please tell me this, that why elder siblings are expected to be more responsible and perfect, than the younger ones! Do you realize, that how much frustrating it is to see your younger sibling laugh at you while you are being scolded…!!? I mean we are kids too, so why this discrimination?

Homework

Doing homework simultaneously is nearly impossible because we are too busy fighting with each other! We want pin drop silence while doing work and if one of us makes even the tiniest of sound, we would start to fight like cats and dogs.

While Eating Food

Alright, so you might be wondering that why we fight while eating? The reason is not big, it’s just we don’t want a single moment of peace at home. We want constant entertainment! And for that, we keep on provoking each other.

Playing

So, what can we play during a lockdown? Of course, mobile games! This is the only time in the entire day when there is peace, as we both are busy with our mobile phones.

Online Class

The online class is too troublesome for us! First, we need to attend our class and then look after younger sibling too, while he/she attends class. I mean it’s not fair, we need to do a lot of different things too!

This is all that I can think of right now, but there are still a lot of small things that are troublesome. Let’s catch up in the next article!