546
KSAvoid This COSTLY Action in Data Pipelines! #shorts #dataengineering
@ksr_datavision
#Deltalake
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36
TESwitching into Data Analytics is one of the most practical career transitions in tech today. But one of the biggest mistakes people make is believing the journey is either very fast or too difficult.
The truth sits in the middle.
In this video, we break down the realistic timeline it takes to move from a complete beginner to becoming job ready in Data Analytics, based on real training experience and industry expectations.
You will understand what to focus on at each stage, how long it typically takes, and what can speed up or slow down your progress.
What You Will Learn in This Video:
• How long it takes to learn Data Analytics from scratch
• The difference between learning tools and becoming job ready
• A realistic month by month roadmap
• The skills you should prioritize first
• When you can start applying for roles
• How projects affect your timeline
• Common mistakes that delay people’s transition
• How consistency impacts your speed
We also explain what happens if you are learning part time versus full time, and how your background in fields like finance, business, engineering, or IT can shorten your learning curve.
If you are planning to switch careers, upskill, or move into a more data driven role, this video will help you set the right expectations and avoid unnecessary pressure.
Who This Video Is For:
• Beginners with no tech background
• Professionals looking to switch careers
• NYSC members and fresh graduates
• Business and finance professionals
• Anyone curious about Data Analytics
Ready to Start Your Data Analytics Journey?
Tech365 offers a practical, hands-on Data Analytics training designed to take you from beginner to professional using real business datasets, projects, and portfolio building.
You will learn Excel, SQL, Power BI, Python, and how to think like an analyst that companies trust.
Subscribe for More Career and Tech Insights
On this channel, we share practical videos on:
• Tech career roadmaps
• High income digital skills
• Realistic salary expectations
• Industry trends
• How to position yourself globally
Subscribe and turn on notifications so you do not miss upcoming videos that can transform your career.
#DataAnalytics
@tech365ng
1.2K
WAExplaining data engineering and data analytics core concepts in easy way.
Data analytics | data engineering | data engineer | delta table | delta lake | data lakehouse | database | databricks|
#dataengineers #dataanalysis #databricks #technology #datalake #datalakehouse
Did you like this explanation?
@waqar_khan_data_engineer
198
DAMistakes while Loading Data
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Avoid these mistakes if you want a reliable and fast data pipelines.
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[data engineer, data engineering, data pipeline, ETL pipeline, big data engineering, spark optimization, SQL optimization, data loading mistakes, data engineer tip]
@datawithdeepankar
23
DAI’m a Sr. Data Engineer first.
I’m a seasoned tech professional with over 13 years in data and analytics and I’m still very much in this field.
I’m not an influencer, and I’m not a course pusher. Anyone who knows me knows that I don’t even like social media like that, nor do I spend a lot of time in this space (ew! lol).
I’m a professional who built a real career on valuable technical skills. If others want to learn those skills, I’m willing to teach but data itself has always been my craft.
It’s my skill. It’s my bread and butter.
And it has afforded my family and me a comfortable lifestyle.
In Q4 of 2025, I made a commitment to myself:
Every quarter in 2026, I will attend a tech conference or intentional learning event.
Not because I need another title or credential but because after 13 years in this space, I know there’s no finish line. This industry is always evolving.
And like any craft, you have to keep sharpening it.
Success doesn’t happen by mistake. The success you’re experiencing today usually comes from what you invested in yourself two or three years ago. That’s why I stay intentional about putting myself in environments that challenge me and keep me learning.
Q1 is already set with SQLCon and FabCon, and I’m excited to share my Q3 conference: the Black Women in Data Summit 2026.
Even after 13 years in this industry, being named a 2025 Woman of the Year – Woman to Watch and a Women in Tech honoree, a member of Women in Technology, serving 8 years as Southeast Program Director of Score, Inc (& a plethora of other organizations); I’m still choosing growth on purpose.
How can I coach and guide others to grow in this space if I’m not doing the same? I don’t coach from the bench. I coach from the field.
I’m still intentionally looking for conferences aligned with my interests for Q2 and Q4.
Nobody is coming to save you.
Nobody is tapping you on the shoulder with a plan.
You have to invest in yourself.
You have to hold yourself accountable.
You have to get in the rooms.
What are you doing today that your future self will benefit from two or three years from now?
@data_analytics_simplified
1.3K
IAEntry-level Data Engineering positions now represent just 2% of all job postings.
The easy work is getting automated.
Junior positions are disappearing.
And that creates a classic catch-22 — how do you become experienced if there’s almost nowhere to start?
But it gets worse.
45% of all data roles now mention AI. Companies want LLMs, RAG, vector databases, ML pipelines.
You’re required to know multiple domains just to compete, making it inaccessible for newcomers.
@iamsoleyman
182
SHIn this video, I explain how Delta Lake handles updates and deletes using a real sales data example.
We walk through:
• How data is stored as Parquet files
• How the _delta_log folder works
• Why multiple transaction log files are created
• How Delta creates new versions instead of overwriting data
• How Spark reads the latest version safely
Delta Lake does not modify files directly.
Instead, it creates new files and records every change in the transaction log.
This is what makes Delta Lake:
Reliable
ACID compliant
Version controlled
#DataEngineering #deltalake #databricks
@shravan_datatalks
0
THHow long will it take me to learn Data Analytics...? 👇
@the_learn_mind
267
COStuck below 15 LPA as a Data Engineer?
It’s not experience.
It’s positioning.
Most engineers stay tool-focused.
High-paid engineers think in scale, cost, and systems.
Which mistake are you making right now?
#DataEngineering #DataEngineer #BigData #TechCareers #LPA
@commit_and_cryy
163
239
DARoadmap to becoming a data engineer#dataengineering #dataengineeringroadmap
@data.with.clarence
113
BIEverything Data Engineers Need to Know
@bite.techie
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