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𝗝𝗼𝗯 𝗩𝗮𝗰𝗮𝗻𝗰𝘆: Marketing Intern (Remote)

💼 𝗥𝗼𝗹𝗲 𝗮𝗻𝗱 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀
As a Marketing Intern, You will work closely with the marketing team and contribute to various aspects of our marketing initiatives.

💰 𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀
This unpaid internship has the potential for conversion to a full-time paid position or a paid internship based on your performance and the availability of suitable opportunities within the company. Successful interns may also receive a letter of recommendation, acknowledging their achievements during the internship, which can be beneficial for future endeavors.

📧 𝗟𝗶𝗻𝗸 𝘁𝗼 𝗔𝗽𝗽𝗹𝘆: https://lnkd.in/ebH_Y6Tn

𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 🎯
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Its step by step process how data flows from data source. ✨

🔅 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗲 : Data source is simply the source of the data.

🔅 𝗗𝗮𝘁𝗮 𝗟𝗼𝗮𝗱𝗲𝗿𝘀 : Data Loader is a application for the bulk import or export of data.

🔅 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲 : Central repository of information that can be analyzed to make more informed decisions.

🔅 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 : Storing of information in a storage medium.

🔅 𝗖𝗼𝗺𝗽𝘂𝘁𝗲 : Information that has been translated into a form that is efficient for movement or processing.

🔅 𝗗𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 : The process of examining data sets in order to find trends and draw conclusions about the information they contain.

🔅 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 : Data visualization is a way to represent
information graphically, highlighting patterns and trends in data.

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𝟳 𝗼𝘂𝘁 𝗼𝗳 𝟭𝟬 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗮𝘀𝗸 𝗦𝗤𝗟 𝗼𝗿𝗱𝗲𝗿 𝗼𝗳 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 💥

♂️ SQL has been an important part when querying data in order to execute meaningful queries to gather well organized data.

🤔 So, the question is what is the order of ex*****on when querying with SQL❓

📌 Here, I'm sharing an interesting way to recall how the ex*****on of SQL queries works in 7 steps

➡ 𝐟𝐫𝐨𝐦 (select right set of tables and joins to get data)
➡ 𝐰𝐡𝐞𝐫𝐞 (apply filters)
➡ 𝐠𝐫𝐨𝐮𝐩 𝐛𝐲 (group or aggregate data)
➡ 𝐡𝐚𝐯𝐢𝐧𝐠 (have logical predicate to filter data)
➡ 𝐬𝐞𝐥𝐞𝐜𝐭 (returns final data)
➡ 𝐨𝐫𝐝𝐞𝐫 𝐛𝐲 (sort the data)
➡ 𝐥𝐢𝐦𝐢𝐭 (limit the number of returned data)

🔰 Window functions play an important role in these order of querying data and helps in applying aggregate functions to calculate, can be used inside 'Select' or 'order by'.

✅ Learn SQL from scratch for FREE here
👉 https://lnkd.in/dPbJTSVS

✅ Looking to prepare for interviews then, Book here
👉 https://lnkd.in/eSM47XvN

🤓 We are looking forward to share more interesting and exciting content to motivate you to deep dive into data!!

🎇 follow Pivot Skool for Data Analytics tip and tricks! 🎇

𝗙𝗼𝗿𝗴𝗲𝘁 LinkedIn ❌

LinkedIn won't guarantee you remote work success.

Here are 7 websites offering USD payments for remote jobs:

1️⃣ RemoteOK

- RemoteOK is a job board that specifically focuses on remote opportunities.

- It allows users to filter jobs based on factors like time zones and skills.

🔗remoteok.com

2️⃣ Wellfound

- Facilitating connections between startups and job seekers.

- Explore 130,000 tech jobs and 27,000 companies.

🔗 wellfound.com

3️⃣ Tryremotely.com

- Explore 17,609 job listings from 15,424 companies.

- Secure a remote job and work from any location.

🔗tryremotely.com

4️⃣ Toptal

Toptal stands as an exclusive network comprising the world's leading freelance software developers, designers, finance experts, product managers, and project managers.

🔗 toptal.com

5️⃣ Nodesk.co

- Discover top remote job opportunities.

- Connect with companies that provide the flexibility to work from home.

🔗nodesk.co

6️⃣ Jsremotely.com

- Find jobs for JavaScript, React, Vue, Node.js, Angular,etc.

- 200+ jobs are released.

🔗jsremotely.com

7️⃣ FlexJobs

- Discover remote job opportunities, whether near your location or globally.

- Presenting 53,779 online job listings from 5,495 companies.

🔗flexjobs.com

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Excel Vs PowerBI 𝗦𝗜𝗠𝗣𝗟𝗜𝗙𝗜𝗘𝗗 ✅

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Credit Nicolas Boucher

𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 you must know as a 𝗱𝗮𝘁𝗮 𝗲𝗻𝘁𝗵𝘂𝘀𝗶𝗮𝘀𝘁 🚀

🔰 Python is an open- source programming language that features all frameworks!!

🤔 What are the important libraries to focus for a data analyst or data scientist performing ML, AI modelling using complex algorithms?

🎯 𝐃𝐚??𝐚 𝐀𝐧𝐚??𝐲𝐬𝐢𝐬 -

🔹
??
🔹
🔹

?? 𝐌𝐋/𝐀𝐈 -
🔹
🔹
🔹
🔹
🔹
🔹

🏷 These aren't limited to but a few important packages that help you build a strong fundamental portfolio with great projects!!

📝 Happy learning folks!!🙂Keep Exploring!! 🔍

⚡ Follow Pivot Skool to stay updated with informative data resources and stories!!

How to 𝗖𝗿𝗮𝗰𝗸 Data Analyst 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 ❓

People who are preparing for Data Analytics Interview We will tell you how many rounds are there !

👉 What type of Rounds ?
👉 What they Ask ?
👉 What they don't ask?

Typically there are three Rounds (80%) but in (20%) You can expect 4 Rounds!

🔔 𝗙𝗶𝗿𝘀𝘁 𝗥𝗼𝘂𝗻𝗱

Its a Technical Based Round Which is Totally Based on your Knowledge in SQL , Basic Python or R Programming , Excel (Lookups, Pivot Tables, Dashboard) , Power BI or Tableau but it depends .They expect a lot in SQL (Questions on Joins , Window Functions, cross Join ,Self Join (Good Command in Group By and Having )) . You must have knowledge in Inbuilt Functions as well !!

🔔 𝗦𝗲𝗰𝗼𝗻𝗱 𝗥𝗼𝘂𝗻𝗱

Its Another Technical Round which is taken by the Manager in this Round they want to check your Analytical Mindset with Little Technical Questions ! Things Asked(Business Case Study for that you must have Knowledge in Business the Company is Doing) They will also Ask You Questions Related to Guesstimates To check are u a good Analyst Person or Not !!

🔔 𝗧𝗵𝗶𝗿𝗱 𝗥𝗼𝘂𝗻𝗱

Its a Managerial + Director Round in which they will ask you Questions on What your Workday looks like in your Previous Organisation . They will ask you to explain your work If you are a Freshers then they will ask you Questions on Strength and Weakness and other Basic Managerial Questions .

🔔 𝗙𝗼𝘂𝗿𝘁𝗵 𝗥𝗼𝘂𝗻𝗱

HR will say you that you are selected as you follow Pivot Skool. What are your Expectation in Terms of Salary !!

Prepare for your interview here: https://lnkd.in/eSM47XvN

Book here for MOCK interview: https://lnkd.in/eZHnGY-U

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𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐕𝐬 𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞 🔱

✅ 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞
A data warehouse is a large-scale, centralized repository of data that is used to support business intelligence activities such as reporting, analytics, and data mining. The main purpose of a data warehouse is to store and manage large volumes of data from various sources in a format that is optimized for querying and analysis.

Data warehouses typically integrate data from various operational systems, such as transactional databases, customer relationship management systems, and enterprise resource planning systems. The data is extracted, transformed, and loaded into the warehouse, where it is organized into a dimensional model consisting of facts and dimensions.

Data warehouses are designed to support complex and ad hoc queries, allowing analysts and decision-makers to gain insights into business operations and performance. They also provide historical data and trends, allowing for better forecasting and planning.

✅ 𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞
Data lake is a large, centralized repository that allows you to store vast amounts of raw, unprocessed data in its native format. Unlike traditional data storage methods, such as data warehouses, data lakes can store any type of data, including structured, semi-structured, and unstructured data.

Data lakes are designed to provide an efficient and scalable way to store large volumes of data, making them well-suited for big data applications. They enable organizations to collect, store, and analyze vast amounts of data from a variety of sources, including IoT devices, social media, and mobile apps.

📍 follow Pivot Skool for more Data Engineering contents!

𝗦𝗤𝗟 𝗷𝗼𝗶𝗻𝘀 made easy 💖

🧠 Here's an amazing self explanatory infographics that depicts the SQL Join clause with each category quite easily.

📍 Types of joins used very often includes -

✔️𝗟𝗘𝗙𝗧 𝗝𝗢𝗜𝗡 - All data from the left table but common data from the right table

✔️𝗥𝗜𝗚𝗛𝗧 𝗝𝗢𝗜𝗡 - All data from right table and common data from the left table

✔️𝗜𝗡𝗡𝗘𝗥 𝗝𝗢𝗜𝗡 - Only common data from both the tables

✔️𝗢𝗨𝗧𝗘𝗥 𝗝𝗢𝗜𝗡 - All the data from both the tables keeping null values with no common keys

✔️𝗨𝗡𝗜𝗢𝗡 - Stack table data on top of one another

✔️𝗖𝗥𝗢𝗦𝗦 𝗝𝗢𝗜𝗡 - All possible combinations of data from both the tables

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❄ Learn 𝗦𝗤𝗟 for 𝗙𝗥𝗘𝗘 here: https://lnkd.in/dPbJTSVS ❄
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𝟲𝟬 𝗺𝗶𝗻𝗱-𝗯𝗹𝗼𝘄𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 𝗯𝗲𝘁𝘁𝗲𝗿 𝘁𝗵𝗮𝗻 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝘆𝗼𝘂 𝗺𝘂𝘀𝘁 𝗴𝗶𝘃𝗲 𝗮 𝘁𝗿𝘆❗️

𝗗𝗲𝘀𝗶𝗴𝗻 𝗧𝗼𝗼𝗹𝘀

FlairAI - https://flair.ai

AutoDraw - https://www.autodraw.com

StockImg - https://stockimg.ai

BoothAI - https://www.booth.ai

ClipDrop - https://clipdrop.co

𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗧𝗼𝗼𝗹𝘀

Eightify - https://eightify.app

Thumbly - https://thumbly.ai

SteveAI - https://www.steve.ai

Clipmaker - https://www.clipmaker.ai

TubeBuddy - https://www.tubebuddy.com

𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗧𝗼𝗼𝗹𝘀

Consensus - https://consensus.app

Paperpal - https://paperpal.com

Trinka - https://www.trinka.ai

Writesonic - https://writesonic.com

Scholarcy - https://www.scholarcy.com

𝗪𝗿𝗶𝘁𝗶𝗻𝗴 𝗧𝗼𝗼𝗹𝘀

AISeo - https://aiseo.ai

Quillbot - https://quillbot.com

Bertha - https://bertha.ai

Simplified - https://simplified.com

𝗖𝗼𝗱𝗶𝗻𝗴 𝗧𝗼𝗼𝗹𝘀

Durable - https://durable.co

10Web - https://10web.io

Akkio - https://www.akkio.com

Replit - https://replit.com

DeepCode - https://www.deepcode.ai

𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗧𝗼𝗼𝗹𝘀

Simplified - https://simplified.com

ContentEdge - https://lnkd.in/dc7JY93f

CopySmith - https://copysmith.ai

Mutiny - https://www.mutinyhq.com

𝗧𝘄𝗶𝘁𝘁𝗲𝗿 𝗧𝗼𝗼𝗹𝘀

Tweetmonk - https://tweetmonk.com

Tribescaler - https://tribescaler.com

Postwise - https://postwise.ai

TweetLify - https://www.tweetlify.co

𝗠𝘂𝘀𝗶𝗰 𝗧𝗼𝗼𝗹𝘀

Boomy - https://boomy.com

Amper - https://lnkd.in/dwN43544

Jukedeck - https://lnkd.in/dVjZnWFK

BrainFm - https://www.brain.fm

𝗖𝗵𝗮𝘁𝗯𝗼𝘁 𝗧𝗼𝗼𝗹𝘀

Yatterplus - https://yatterplus.in

Typewise - https://www.typewise.app

Quickchat - https://www.quickchat.ai

Cohere - https://cohere.com

Kaizan - https://kaizan.ai

👉 Follow If you like to show your support!

Shoutout to your 𝗺𝗲𝗻𝘁𝗼𝗿💡

In the comments below, mention your mentor and share how they have made a significant impact on your career. Whether it's their insightful advice, support, or the doors they opened for you, let's celebrate their influence! 🎉

𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽 is like having a trusted guide by your side on your professional journey. It's a relationship where an experienced mentor shares their wisdom, knowledge, and insights with a mentee, helping you navigate challenges, develop skills, and achieve your goals.🌟

If you don't have a mentor yet,

Find your mentor here 👉 https://pivotskool.com/

✨ Follow Skool for more career tips!

📚 𝗕𝗲𝘀𝘁 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗕𝗼𝗼𝗸𝘀 📚
(Amazon links are in pinned comment)

💎 𝙎𝙩𝙖𝙩𝙞𝙨𝙩𝙞𝙘𝙨 𝙖𝙣𝙙 𝙋𝙮𝙩𝙝𝙤𝙣
1. Practical Statistics by Peter Bruce, Andrew Bruce, Peter Gedeck
2. Python for Data Analysis by Wes McKinney

💎 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙄𝙣𝙩𝙚𝙡𝙡𝙞𝙜𝙚𝙣𝙘𝙚 𝙖𝙣𝙙 𝘿𝙖𝙩𝙖 𝙑𝙞𝙨𝙪𝙖𝙡𝙞𝙯𝙖𝙩𝙞𝙤𝙣
3. AI-Powered Business Intelligence by Tobias Zwingmann
4. Storytelling with data by Cole Nussbaumer Knaflic
5. The Definitive Guide to DAX by Marco Russo and Alberto Ferrari

💎 𝙈𝙖𝙘𝙝𝙞𝙣𝙚 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙖𝙣𝙙 𝘿𝙚𝙚𝙥 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜
6. Hands on Machine Learning with Scikit-Learn, Keras and TensorFlow by Aurélien Géron
7. Machine Learning with Pytorch and Scikit-Learn by Sebastian Raschka, PhD, Hayden Liu, Vahid Mirjalili, PhD, Dmytro Dzhulgakov
8. Deep Learning with Python by François Chollet
9. Deep Learning with TensorFlow and Keras by Amita Kapoor, Antonio Gulli, Sujit Pal

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What is your best data science book?

Please let me know on the comment sections 📩
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