#Information Management

From data models to SQL basics, understanding Database Management Systems is the backbone of every developer’s journey. Key concepts covered: Data Models Normalization SQL (DDL & DML) Keys & Constraints ACID Properties Strong DBMS knowledge = Better problem solving + Efficient data handling Follow @code_with_yashhhh for daily Python tutorials #code_with_yashhhh #fypppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp #python #explorepage✨ #reelitfeelit

I won’t be mad if you copy this entire roadmap… #dataanalyst #dataanalysis #dataanalytics #data #analyst #techjobs #breakintotech #wfh #workfromhome #wfhjobs #remotejobs #remotework #excel #sql #tableau #python

Information Technology Information Systems #informationtechnology #informationsystems #itjobs

Ever wondered how companies prove they’re secure? This is where ISO 27001 and the ISMS Manager come in. In this episode of Decrypting GRC, I break down what an ISMS Manager does and how standards like ISO 27001 come into play. #cybersecurity #infosec #computerscience #techjobs #tech

50 important Cammands for IT professionals #cybersecurity #networking #linux #aws #devops

Comment “TIPS” if you want my full guide + insider breakdowns on what interviewers look for. If you don’t have these three projects in your portfolio, you’re not ready to stand out. Most beginners build dashboards… but these are the projects that actually get you hired. #dataanalytics #dataanalyst #analyticscareers #datascience #businessanalytics dataportfolio learnanalytics careercoach earlycareer techcareers sql excel alteryx breakingintodata firsttechjob

Biggest Myth In Data Analytics Coding helps, bur its’s Not mandatory to start So stop overthinking and start learning And if you want more details about this course then check out IIM SKILLS Link in the bio #explore #edtech #dataanalytics #onlinecourse

This one is for my fellow geospatial peeps out there 📍🙌💕 Follow @maggieindata along my journey breaking into data science as a new grad with my bachelor’s in statistics and geography. I share early career and interview tips, working in tech shenanigans, day in the life videos, and regular Q&As ✨

You cannot become a data analyst if you can’t do these things (shared the tools I use in the end)🔥🔥 Follow @onestopdata for data related content! ✅The most imp thing data analysts do is to understand the business requirements. (1) Gathering Data This means collecting data from different sources. Many a times this is done in collaboration with data engineers and architects hence usually the data analyst doesn’t have to do a lot in this. (2) Cleaning Data Going through the data and trying to understand it, making corrections where needed such as removing outliers or data that should not be included in the analysis. This step can take a lot of time, but understanding the data is crucial before you start to process it. (3) Processing data The data processing part of the process is where I use my skills and tools to analyze the work and come up with solutions for the problem at hand. (4) Creating reports for business leaders As an analyst, a lot of my time goes into creating and maintaining reports/dashboards for stakeholders and business leaders. This means showing the metrics and KPIs in the best manner possible to help drive business decisions. The best analysts are those that can use data to tell a story. (5) Collaborating with people This one is my favorite! As a data analyst, you work with many people across departments, both senior and junior. You’ll also likely collaborate closely with other people who work in data science like data architects and database developers. Tools I use: Excel,PowerBI,SQL and Python(sometimes) #dataanalytics #onestopdata #datacleaning #dataprocessing #dashboard #reports #sql #powerbi #excel #python

Build a data cleaning & reporting workflow in ✌🏽 minutes (without code!) #KNIMECollab In this example, I’m using KNIME to build a very simple data cleaning & reporting workflow. This is the most common framework I’ve used for reports: 1. Extract data 2. Clean / transform the data 3. Load data I just started using KNIME recently, and it is so powerful and versatile. It’s designed for Data Analysts & Data Scientists in mind, and they’re already integrated with many different data tools, like Excel and SQL databases. Plus, when you get KNIME Pro, you can schedule the workflows you build. No need to keep running the same processes manually! If you are in one of those roles, I highly recommend that you check it out! #datascience #dataanalytics #automations

Statistics is NOT just for statisticians. It’s the secret weapon of every Data Analyst. Each dataset hides a story, and distributions help us decode it. 👉 A quick cheat sheet for you (save this!): 1. Normal = classic bell curve 2. Uniform = equal chance 3. Binomial/Bernoulli = success vs failure 4. Poisson = rare events 5. Log Normal = skewed data 6. Gamma/Beta = flexible shapes 7. Geometric = time until first success ⚡ Knowing the right distribution = better insights, smarter decisions. Ask yourself: What story is my data’s distribution telling me? Which of these do you use most? -- Follow @jayenthakker and @metricminds.in ➕ Dedicated to helping aspiring data analysts thrive in their careers. -- #dataanalytics #datascience #data #metricminds #datavisualization #analytics #artificialintelligence #python #ml #careers #sql #careerswitch #trendingreels #foryoupage #learning

Number 3 is very important. ​ ​ @microsoft365 will foil your micromanagement strategy. ​ ​ Link in bio if you still want to try out Microsoft 365 Copilot #Microsoft365Partner​