EMMIE Collective’s Post

To some, Austen's insights might sound like Greek, but for database admins, it’s music to your ears! Austen Brown dives deep into why maintaining a clean donor database is crucial for your nonprofit’s success. Because let’s face it—keeping your data spotless is a challenge. From outdated addresses and incorrect emails to those “Name” typos, it can feel like a constant battle. But before you think about hitting the reset button, what if there was a more efficient way? 🤔 Don’t miss this chance to transform your data management strategy: https://hubs.ly/Q02KV2cC0

Data loaders are awesome, but they can also be intimidating if you haven't used them before. In under 20 minutes, learn the data loader essentials you need to start writing your own: https://buff.ly/4ck89YS

Halloween may be behind us, but you might be feeling spooked by the thought of large scale data migrations—they’re far from a simple copy and paste. Luckily, our team can help with that 😊 ➡️ https://hubs.li/Q02Ws2f50 #acceleratinggrowth

Hello Everyone 👋 🚀 Day 61 of my 100-Day Data Structures and Algorithms Challenge! 📚 Today, I ventured into the world of linked lists, starting with an introduction to linked lists by implementing a function to create a linked list from an array of positive integers. Here's a summary of what I accomplished: 1️⃣ Introduction to LinkedList: I began by understanding the fundamental concept of a linked list and its structure. Then, I implemented a function that takes an array 'Arr' of size 'N' consisting of positive integers as input. The task was to create a linked list from the given array and return the head of the linked list. The head of the linked list corresponds to the first element of the array, while the tail corresponds to the last element. By successfully creating a linked list from the given array, I gained insight into how linked lists are constructed and how they can be utilized in various scenarios. As I delve deeper into the world of linked lists, I'm excited to explore more advanced concepts and problem-solving techniques to further enhance my understanding. Let's continue this journey of learning and exploration, embracing the challenges and opportunities for growth that lie ahead! 💡💪 #100DaysDSAChallenge #DataStructures #LinkedLists #LearningAndDevelopment 🔗📝

DB Sharding Fairy tale: The Art of Breaking Up to Scale Up Once upon a time in the land of databases, a single monolithic database felt bloated and overwhelmed. It was the guardian of all data, but time and users were no friends. The more it grew, the more it slowed down, much like a fridge overstuffed with leftovers. Enter the hero in our tale: DB Sharding! Sharding is like dividing responsibilities among siblings. Instead of relying on one grumpy database, we split the data across multiple databases, or "shards." Each shard takes on a portion of the data, like delegating chores—one shard organizes the shoe closet, another guards the cookie jar. Not only does sharding prevent the database from resembling a tangled yarn ball, it also boosts performance. When users flood in, each shard can handle their requests without elbowing for space. Think of it like traffic control; instead of funneling all cars into one lane, you open multiple lanes for smooth sailing. Of course, just like assigning chores at home, sharding requires careful planning. Ever tried telling your brother to wash the dishes only to find he hoarded all forks in his room? In sharding, improper data distribution can lead to similar chaos. But with careful management, it's the perfect solution for when your single database has bitten off more than it can chew. So, worry not! When your database starts huffing and puffing, consider sharding. It just might be the breath of fresh air your system—and your users—need. Sharding: because sometimes breaking up is the best way to stay together! #DB #DBOptimization #DBScaling #Sharding #HorizontalScaling Also you can read my previous article about another way of DB optimization here: https://lnkd.in/eZCf2-y3

What is the difference between COUNT(*) and COUNT(1) in SQL? Let’s break it down 👇 → 𝗪𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗱𝗼 - COUNT(*): Counts all the rows in a table, regardless of NULL values. - COUNT(1): Also counts all rows. The 1 is just a placeholder constant. → 𝗪𝗵𝗮𝘁 𝗿𝘂𝗻𝘀 𝗳𝗮𝘀𝘁𝗲𝗿 - COUNT(1) might be slightly faster, but the difference is almost unnoticeable. → 𝗪𝗵𝗮𝘁 𝗿𝗲𝗮𝗱𝘀 𝗯𝗲𝘁𝘁𝗲𝗿 - COUNT(*) is clear and straightforward. - COUNT(1) might be less immediately obvious. 𝗜 𝗮𝗺 𝗧𝗘𝗔𝗠 𝗖𝗢𝗨𝗡𝗧(*)! Because it's more clear and straightforward! What is your team? Comment below! 👇 ------------------------------------------------------- Click 🔔 on my profile to get notified on all my new posts.

Happy First Day of Spring! ☀️ With warmer days coming soon, many of us are making spring cleaning checklists to address the things we haven’t dealt with all winter. If you haven’t recently backed up your personal or small business data, I highly recommend adding data backups to your to-do list this spring! Regular backups are one of the most effective ways to prevent large data losses. My team and I at Cheaper Than A Geek offer data backup services for small businesses to make this process even easier for you, so you have more time to check everything else off your spring cleaning list! Learn more about our data backup services! ⬇️ https://bit.ly/3qwV1gA #DataBackUps #FirstDayofSpring #OutsourcedIT

Do you ever use the OBJECT_PICK or OBJECT_DELETE functions in Snowflake? When working with semi-structured data, we often want to use only specific keys and values. These functions can be handy for materializing a smaller subset of your semi-structured data or implementing dynamic data masking policies. I'll share the docs and a Medium article I found in the comments. Here's an example of how they work!

Tom Freedman, Director, looks forward to presenting "NULL: Much Ado About Nothing" at the New Stars of Data event on April 5.     For data practitioners, working with NULL is inevitable. Its odd nature can lead to bugs and unexpected results for even the most experienced data pros. Tom will discuss what NULL is and isn't, why it needs special handling and consideration, and some best practices in SQL Server. Join Tom to hear more or connect with him on LinkedIn to discuss further.