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Generation Zoom children learning about their roots

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This text is an excerpt from the Chapter “The Generation Zoom Classroompublished in the book “Aftershocks & Opportunities: Scenarios for a Post-Pandemic Future” by Fast Future Publishing. If you enjoy the text, feel free to read the full chapter and the entire collection of chapters, available on Fast Future Publishing’s store and on Amazon. Thank you for your support!

History Class, MLK High School, January 2037

“Let’s all turn our H-Story pads to page 183, where we left off last time.”

Sounds of virtual pages turned filled the classroom.

“As you might recall, to combat the spread of COVID-19, shelter-in-place was imposed in multiple States across the U.S., starting in March 2020 with California and New York. Unfortunately, while the measures did curb contamination and death rates, they remained insufficient to prevent the continued spread. The primary source of contamination were grocery shopping and healthcare facilities. Consequently, new regulations were put into place restricting days and times people could go shopping. Can anyone explain how it was established?”

“First, the elderly could enjoy dedicated timeslots – typically early morning,” ventured Rick from the first row. “Then last name became the main criterion, so families could go together”.

“Exactly! This new restriction, although not strictly enforced, did help. Numbers started to plateau a bit, and people got hopeful again. But then two independent events took place. 

The first was the premature attempt to relaunch the economy, which had come to a halt almost overnight. Non-essential businesses had to close, and the unemployment rate skyrocketed due to a combination of firings and hiring freezes. To avoid further deterioration of the situation, workers were incentivized to go back to work and minimal safety equipment was distributed in the workplace – masks, gloves, sanitizer. Shelter-in-place was eventually lifted in multiple States, and schools reopened before the situation had completely cleared.

Secondly, even before the vaccine for COVID-19 was manufactured, a derived strain of COVID emerged. Pharmaceutical efforts were redirected towards the development of a broad-spectrum multi-respiratory syndrome vaccine destined to protect from subsequent COVID variations. This, combined to the rushed reopening, had dreadful consequences, and  infection rates and death toll reached new highs.”

Andrea paused to catch reactions from the audience, the so-called ‘generation Zoom’ or Zoomers. Despite being part of the boom in births following the onstart of the pandemic, they seemed oblivious to the dramatic events surrounding their conception.

Source: https://siliconhumanism.home.blog/2020/07/31/generation-zoom-children-learning-about-their-roots/

Big Data

Join Hands with Instagram’s New Algorithm to Boost Your Business’s User Engagement

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👉 Most people are not at all happy with the latest 📸 Instagram algorithm. However, if you want to make the most of your business, you should understand how it works. The trick here is you must work with its algorithm and not go against it here; it is easy for your know-how. 👇🔻

🚩This post will guide you on how the 🆕 new Instagram algorithm works and how you can use it for the advantage of your business-

How does the new Instagram algorithm work?

The new 📸 Instagram ♀️ algorithm is a mystery to many users on the platform. It no longer functions at a slow pace as it did in the past. To score high on Instagram today, you need to be extremely diligent as a business owner. The algorithm needs to be fully optimized so that you get success in the platform. So, read and remember the following factors to help you determine how your posts can perform well to boost user engagement and sales revenue for your business with success-

The volume of social engagement you receive -: Note, your posts with the maximum number of shares, views, comments, etc., will rank high in the Instagram feed over others. When your post receives a lot of comments and likes, the Instagram platform gets a signal that it is engaging to users and has high-quality content. It wants more users to see it, and the algorithm on the platform will display it to other users online.

However, here again, there is a catch. It is not only the engagement that Instagram considers now; it is how fast your Instagram post engages the readers in some cases. Trending hashtags on Instagram, for instance, is the best-known example of the above. The volume of engagement you get for your business posts is important; however, how quickly you get this engagement is even more important!

👉▶Tip- You should discover when the best time of the day to post is. In this way, you can schedule posts targeted at that time only. You should post when most users can see it. This increases your chances of boosting engagement faster, and the Instagram algorithm as it knows what somebody likes on Instagram and will take over from here to share it with those users who will ✌ ⚡ like, share and comment on your post.

How long are people looking at your post on Instagram -: If you see the algorithm that Facebook uses, it takes into account how long users look at your post and spend time interacting with its content. Instagram is no different! Its algorithm will take a look at the duration of time that users spend on your post too. This is again, another important factor that Instagram uses to boost posts.

👉▶Tip- Here, you should craft a great 📸 Instagram caption for your post to boost user engagement. If your Instagram caption is engaging, users will want to read it or click on the button that says “more” to spend more time on your post, and in this way, you can boost more engagement with success on  📸 Instagram.

This is why Boomerangs and videos are generally posted in the 📹 video format. This makes them perform well with the Instagram algorithm. Users take more time to watch them toll the end. Another great way for you to make users stay on your posts is to swipe up CTA action for them to view more. This is another great strategy you can use for your business to boost engagement.

When did you post your photo?-: This is another factor that influences how the 📸 Instagram algorithm works for your business is determining the time of the post. It depends on how often you use the 📲 app. In the past, the algorithm used to give you insights into the recent posts; however, if you tend to log on to Instagram just a few times in one week, it will show posts that have been posted recently. You might even get likes from a previous post that you published a few days ago. The target here is to keep users updated on the posts they might have missed due to the fact that they did not log in regularly.

👉 This means that users can see your posts now for longer periods.

The sort of content you post also influences engagement – Think about if 📸 Instagram only focused on content with the optimal engagement; users would only see that content every time they logged into 📸 Instagram. However, this is not the case with the Instagram algorithm.

For instance, the content 👥 users’ genre searches for in the platform also influence the algorithm of how Instagram works. If a user is a fan of sports, says the NBA and sees that genre of content regularly, Instagram will immediately catch on to this and bring the user more similar content related to sports and the NBA. It knows that the user will be interested in such posts and perhaps bring news and updates of the LA Lakers to boost 👤 user engagement and satisfaction.

Accounts that users search for -: Like the above, the accounts that users search for also determines how the 📸  Instagram algorithm works. This is why when users search a specific 🧾 account many times; Instagram will bring more such content from other accounts to that user. This is why they see it often in their Instagram feeds.

From the above, it is evident that if you want to work with the new Instagram algorithm, you must understand how it works and optimize your posts to help it boost your business. In the past, the feed on Instagram was chronological; however, things have changed now.

🟥 So, ensure that your CTA is strong; you use the right hashtags, post at the best time, and make your feed on Instagram as attractive as possible. In this way, you can boost user engagement, lead conversions, sales, and of course, gain a strategic edge in the market as well.

↘ Source: Ron Johnson. Ron is a Marketer. He always shares his tips on trendy marketing tricks. He always implements new tricks in his field.

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Big Data

What are the differences between Data Lake and Data Warehouse?

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Overview

  • Understand the meaning of data lake and data warehouse
  • We will see what are the key differences between Data Warehouse and Data Lake
  • Understand which one is better for the organization

Introduction

From processing to storing, every aspect of data has become important for an organization just due to the sheer volume of data we produce in this era. When it comes to storing big data you might have come across the terms with Data Lake and Data Warehouse. These are the 2 most popular options for storing big data.

Having been in the data industry for a long time, I can vouch for the fact that a data warehouse and data lake are 2 different things. Yet I see many people using them interchangeably. As a data engineer understanding data lake and data warehouse along with its differences and usage are very crucial as then only will you understand if data lake fits your organization or data warehouse?

So in this article, let satiate your curiosity by explaining what data lake and warehousing are and highlight the difference between them.

Table of Contents

  1. What is a Data Lake?
  2. What is a Data Warehouse?
  3. What are the differences between Data Lake and Data Warehouse?
  4. Which one to use?

What is a Data Lake?

A Data Lake is a common repository that is capable to store a huge amount of data without maintaining any specified structure of the data. You can store data whose purpose may or may not yet be defined. Its purposes include- building dashboards, machine learning, or real-time analytics.

data warehouse data lake

Now, when you store a huge amount of data at a single place from multiple sources, it is important that it should be in a usable form. It should have some rules and regulations so as to maintain data security and data accessibility.

Otherwise, only the team who designed the data lake knows how to access a particular type of data. Without proper information, it would be very difficult to distinguish between the data you want and the data you are retrieving. So it is important that your data lake does not turn into a data swamp.

data warehouse data lake

Image Source: here

What is a Data Warehouse?

A Data Warehouse is another database that only stores the pre-processed data. Here the structure of the data is well-defined, optimized for SQL queries, and ready to be used for analytics purposes. Some of the other names of the Data Warehouse are Business Intelligence Solution and Decision Support System.

What are the differences between Data Lake and Data Warehouse?

Data Lake Data Warehouse
Data Storage and Quality The Data Lake captures all types of data like structure, unstructured in their raw format. It contains the data which might be useful in some current use-case and also that is likely to be used in the future. It contains only high-quality data that is already pre-processed and ready to be used by the team.
Purpose The purpose of the Data Lake is not fixed. Sometimes organizations have a future use-case in mind. Its general uses include data discovery, user profiling, and machine learning. The data warehouse has data that has already been designed for some use-case. Its uses include Business Intelligence, Visualizations, and Batch Reporting.
Users Data Scientists use data lakes to find out the patterns and useful information that can help businesses. Business Analysts use data warehouses to create visualizations and reports.
Pricing It is comparatively low-cost storage as we do not give much attention to storing in the structured format. Storing data is a bit costlier and also a time-consuming process.

Which one to use?

We have seen what are the differences between a data lake and a data warehouse. Now, we will see which one should we use?

If your organization deals with healthcare or social media, the data you capture will be mostly unstructured (documents, images). The volume of structured data is very less. So here, the data lake is a good fit as it can handle both types of data and will give more flexibility for analysis.

If your online business is divided into multiple pillars, you obviously want to get summarized dashboards of all of them. The data warehouses will be helpful in this case in making informed decisions. It will maintain the data quality, consistency, and accuracy of the data.

Most of the time organizations use a combination of both. They do the data exploration and analysis over the data lake and move the rich data to the data warehouses for quick and advance reporting.

End Notes

In this article, we have seen the differences between data lake and data warehouse on the basis of data storage, purpose to use, which one to use. Understanding this concept will help the big data engineer choose the right data storage mechanism and thus optimize the cost and processes of the organization.

The following are some additional data engineering resources that I strongly recommend you go through-

If you find this article informative, then please share it with your friends and comment below your queries and feedback.

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Source: https://www.analyticsvidhya.com/blog/2020/10/what-is-the-difference-between-data-lake-and-data-warehouse/

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Big Data

KDnuggets™ News 20:n40, Oct 21: fastcore: An Underrated Python Library; Goodhart’s Law for Data Science: what happens when a measure becomes a target?

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KDnuggets™ News 20:n40, Oct 21: fastcore: An Underrated Python Library; Goodhart’s Law for Data Science: what happens when a measure becomes a target?

fastcore: An Underrated Python Library; Goodhart’s Law for Data Science and what happens when a measure becomes a target?; Text Mining with R: The Free eBook; Free From MIT: Intro to Computational Thinking and Data Science; How to ace the data science coding challenge


Features |  Events |  News |  Tutorials |  Opinions |  Tops |  Jobs  |  Submit a blog  |  Image of the week

This week on KDnuggets: learn about an underrated Python library; find out what happens when a measure becomes a target; grab a free ebook on text mining with R; take a free course on computational thinking and data science from MIT; learn how to ace the data science coding challenge; and much, much more.

 Features

 Events, Webinars, Meetings

 News

 Tutorials, Overviews

 Opinions

 Top Stories, Tweets

 
 Jobs

  Image of the week

Goodhart’s Law for Data Science and what happens when a measure becomes a target?
From Goodhart’s Law for Data Science and what happens when a measure becomes a target?

Source: https://www.kdnuggets.com/2020/n40.html

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