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Applications of Data Engineering

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In a previous blog post about data engineering, we went through several many concepts related to data engineering such as data modeling, and then we went through different types of databases, for example, relational databases and we also got a glimpse of relational as well as NoSQL databases. And in today's blog post we will be writing about data engineer applications. Which are basically the use cases of data engineering 1st let's see what data engineering applications mean; so basically when we have data and we have engineered it then there are several things that we can do with that data and these things that we can do with processed data are the use cases of the data engineering. For example: If we have filled our containers with the data then it's not of any good use if it is not clean and well-formed. If your data is well-formed and if there are no logical mistakes, missing values, and garbage then we can easily perform the use cases and applications of data enginee...
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Data Engineering Tools

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   Data is a new oil. To channelize this data we need proper pipelines. These pipelines are mostly called ETL or data pipelines.  There are various tools out there to work out these Extract, Transform, and Load (ETL) operations.  Some of the scripting tools are:  - Python - SQL and NoSQL Apache provides a wide range of products that can be used as Data Engineering tools.  Some of the amazing apache DE services comprised of; - Hadoop - Spark - Kafka - Cassandra - Hive In addition, some cool DE tools are: - Tableau - Talend - MapReduce These DE tools provide a way to manage the data pipelines in a more effective, efficient, and better way.  Almost every Data-Oriented company in the corporate sector is highly dependent upon these technologies. They are leveraging many of the above-mentioned mechanisms for promising Data Services and Architecture. That's it for today. Hope you have enjoyed this article. If you want to know more about data or software relat...
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Good Pieces of Advice for Freshers

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To let you know a few useful things, I asked some experienced people, and here is what they have for you... Be open to changes. Focus on improving your soft / people skills. It will be hard sometimes but believe in yourself. You have got it. ( Rahat-Undergraduate ) Try to do good in quizzes and OHTs (One hour test or mids) cause when finals don't go well, these can help in getting good gpa which are comparatively easy then finals. ( Ayesha Munir-Undergraduate )   A few years later when you would look back at this time, GPA won't make you happy, but the memories of these 4 years will. Your career is important but so is having a good time. So work hard, party harder! ( Haris-Undergraduate ) From the start try to build your connections with seniors because they know more than you and.. are best counselors.. Focus on your quizzes and assignments because they are the building blocks of your Grade.. Your Good Image play some important part for favoritism points in exam....
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Relational Data Model

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In the previous blog post, we covered Data Modeling. We have seen that data modeling is really important before jumping into predictive modeling.  In this article, we will cover the Relational Data Model (RDM). Let's start from the very basics, relational means anything which is linked with some other thing. This link is called "Relationship". In RDM or RM there are major three types of relationship cardinalities (also called Multiplicities or Cardianalities): 1. One to one 2. One to many 3. Many to many We can understand these with the help of a few simple examples;  One to one: One department has one manager. One to many: One class has many students. Many to many: Many teachers can teach many students. Okay, so we have got an abstract overview of the term " Relational ", now the next thing is " Data ", data covers everything, anything... And finally, " Model " means something in the form of a template, design, a kind of blueprint.  To store...
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NoSQL database

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  Data is everywhere, it is expanding with each passing day. Relational Database systems are kind of fixed and static. When we have something in abundance and without any standard formation, then the tables of relational database systems cry out.  So what to do with so many data integrations from several structured as well as unstructured sources. Well, the answer is to go for NoSQL (Not Only SQL). SQL is a structured query language that is used to query Relational Databases. However, NoSQL database does not contain data in the form of relations. Most of the NoSQL databases follow the JSON type structure to store data.    Formal Definition:      Guru99  provides a pretty nice definition for NoSQL databases: " NoSQL Database  is a non-relational Data Management System, that does not require a fixed schema. It avoids joins and is easy to scale. The major purpose of using a NoSQL database is for distributed data stores with humongous data stora...
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Data Modeling

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source: https://searchdatamanagement.techtarget.com/definition/data-modeling A wise person once said a picture is worth a thousand words . In real-world data is not just a few rows of excel sheet, yet it comprises several billion rows expanded through hundreds  of tables. A table is usually made up of rows and columns. Each table represents an Entity . Entity means an Object or thing. That Entity has several properties called Attributes . Those attributes represent the qualities or characteristics of the entity. Since there is more than one entity, so there should be a Relationship between those entities. If we look at the tables we cannot get a clear idea of the relationship between several tables/Entities. Hence, we need to represent the tables/data in the form of a picture or a flow graph. That flow graph or Entity-Relationship diagram is called a Data Model .  Data Modeling is a technique to represent how the tables are related to each other and to represent the s...
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E-Commerce : Platforms

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Before digging into E-commerce platforms, let's first understand what an E-commerce actually is? E-Commerce... According to the Tokenization Rule , E-commerce is the combination of "E" and "Commerce".  The word Commerce means trade or buying and selling of items, goods, services, hardwares and, softwares... etc. And " E " stands for "Electronic", electronic means something like electricity, like signals, like something in the form of electrons (at lower level).  Image Source So, the word " E-COMMERCE " means: " A type of trade, that is done using electronic devices (computer, mobile or ATM machines etc). "   And to achieve electronic commerce, what's the most important thing? think over it!  Yeah that's correct! your own Internet is the most important thing to do E-commerce.  Major areas of E-commerce are: On-line shopping or retailing On-line bidding or auction On-line soft...
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A Survey of the Final Year University Students

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I don't know what should be the title of this blog post, but let's call it " A survey of the final year university students ". Pretty long title, huh? Okay, let me tell you about this survey... The story behind this thing: Well, one day I thought about writing a post on Facebook to ask people about their sentiments and reviews regarding the final year of university life, then another thought knocked my head to write a full blog post on this topic. Then I disseminated a google form for this purpose. The google form was saying: "Hello, final semester people! I thought to collect reviews of 2020 graduates specifically of NUST and other IT universities. I am planning to add these to my blog post. Please take a few seconds to fill this form, thank you." So that was a brief story behind this whole thing, Now let's have a look at the most awaited questions and the corresponding responses...  Question#1:  Do you feel like a better hu...
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1-Machine Learning : Start...

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John went to the cafeteria 10 times at 1:00 P.M. on 10 Fridays, each time the cafeteria was closed at that particular time. John decided not to go to cafe at 1:00 P.M. on Friday because the cafe will be closed.  But wait! How did John know that the cafe will  also be closed on next Friday at 1:00 P.M.??? Yes, you are absolutely right.  "John Learned from his Experience that the Task of going to the cafeteria at 1:00 P.M. on Fridays resulted in waste of time, since the cafe was closed on each Friday, so it will Perform the same on the next Friday." In the above scenario, John learned something so we can call it " John Learning ". Similarly, if we replace John with some sort of Machine, that can learn from the Experience or from the History about how the tasks were performed in the past given certain situation. Such that the Machine will perform the same if the same task happen again in near future. Then this will be called as Machine Learning. To mak...
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