Alliance of Professionals & Consultants, Inc. (APC)’s Post

Understanding Database Normalization in Simple Terms Database normalization is all about making your data clean, organized, and efficient. Here’s a quick breakdown: 1. What is Normalization? Normalization is the process of structuring a database to reduce redundancy and improve data integrity. It ensures that your data is stored logically and efficiently. 2. Why Normalize? By normalizing, you avoid duplicate data, minimize the risk of inconsistencies, and make your database easier to maintain and scale. Imagine having customer details stored in multiple places—updating one without the other could cause serious issues! 3. The Normal Forms: Normalization typically involves several steps known as "Normal Forms": - 1NF (First Normal Form): Ensure that each column contains atomic, indivisible values. - 2NF (Second Normal Form): Make sure all non-key attributes depend on the primary key. - 3NF (Third Normal Form): Eliminate transitive dependencies where non-key attributes depend on other non-key attributes. Why It Matters: Normalization helps keep your database clean and efficient, making it easier to manage and scale as your data grows. It’s a critical step in creating a robust and reliable database system. #databasenormalization #dataintegrity #databasedesign #techinsights #recruitment #hiring #dataengineering #softwaredevelopment #techcareers #jobopportunities #linkedin

Do you work in Data Engineering or Software Engineering? Have you built your own system of alerting? ⚠ If the answer to both of these is yes, I would not be surprised Alerts are so fundamental to the success of an organisation. But getting accuracy is hard. Not enough alerts mean you drop the ball - stuff breaks, you are the last to find out. No trust, and at worst you actually cause meaningful losses to P&L. Too many alerts, and you're essentially a SOC Analyst, manually sifting through logs all day to work out what you need to do just to keep your head above water In data, an enormous problem is that often the people that need to be alerted by data issues sit across different teams, both within technical domains like data but also business departments To take a simple example anyone can understand - if your Salesforce export is broken, how can you as a data professional alert your Head of Sales that their Dashboard / Analytics is stale and that you're looking into it and not to panic? 😅 The answer is not to send Salesforce alerts to your Head of Sales. The answer is to have Data as a Product and a configurable alerting system where Owners (you) and Stakeholders (them) can get alerted when different things happen. By understanding the dependencies or LINEAGE between the visible part of Data Products and the Data pipelines that underpin them, you can finally avoid alert fatigue and get notified when the IMPORTANT stuff breaks. Some exciting announcements to come from Orchestra #dataengineering #datawarehouse #snowflake #alertfatigue

There is just soooo much I want to say on this - but for now I will refrain myself and only say this: THIS is a real problem - and in my experience most places actually have no/too few alerts but also the other side of that spectrum all alerts go to the central team - even for purely business oriented issues (consistency tests: does these numbers make sense), which in turn as Hugo Lu explain make the poor central team responsible for non-technical issues. A layered approach with different targets etc is certainly needed. Better yet combined with some type of watermarking of output for non-blocking failures etc. Spot on!

Utility vs IQ: Redefining Data Center Hiring IQ is like the popular kid in school - they're smart, know it, and are not afraid to show it. On the other hand, utility is like the class clown - they might not be the smartest, but they sure know how to make people laugh and get the job done. So, who should you choose for your data center dream team? Well, it depends on what you're looking for. IQ is your go-to if you want someone who can solve complex problems and make your data center the envy of all the other data centers. But utility is your best bet if you're looking for someone who can keep the data center running smoothly and make everyone feel like they're part of the team. But why not have both? After all, who wouldn't want a popular kid who can also make you laugh? Ultimately, the perfect data center employee is a mix of IQ and utility. They're intelligent, funny, and know how to do the job. And who knows, they'll even bring some humor to those long, boring data center meetings. Enjoy your weekend, Brian- P.S. Are Utility, IQ, or both required for you in hiring in the #datacenter? #UtilityVsIQ #DataCenterHiring

DVA is not associated with this job posting Senior Data Engineer https://lnkd.in/gW9YTA4K Here's what you'll do: Data Pipelines & Warehousing: Design, build, and maintain robust data pipelines for both batch and stream processing, ensuring efficient data movement throughout the system. Develop and manage our ClickHouse-based data warehouse, optimizing data storage and retrieval for large datasets. Data Analysis & Insights: Leverage SQL and Python to analyze diverse datasets, extract valuable insights, and translate them into actionable recommendations. Implement and maintain high data quality standards with robust data quality assurance practices. Cloud & Collaboration: Utilize cloud technologies effectively for data pipeline orchestration, processing, and storage, optimizing for both performance and cost-efficiency. Collaborate closely with cross-functional teams to understand data needs and deliver solutions that align with business objectives. Communication & Knowledge Sharing: Communicate complex data concepts and insights clearly and concisely to both technical and non-technical stakeholders. #techjobs #jobsearch #hiring #technology #careers #jobopportunities #jobhunt #jobseekers #jobmarket #jobposting #jobopening #jobalert #joblisting #jobvacancy #jobseeking #jobseeker #jobboard #jobs #hiring #careers #employment #jobopportunities #jobposting #joblisting #jobhunt #cfbr #jobmarket #jobadvertising #jobrecruitment #jobnetworking #jobplacement #jobvacancies #business #work

We are #hiring Data Engineer for a leading global company. If you are interested, please send your resume to ksmohan@hiringessential.com Job Title: Data Engineer Duration: Long Term Location: Aurora, IL/Dallas, TX Job Summary: Work with limited supervision to support data engineering and data analytics solutions. Provide design guidance and implementation for end-to-end analytic solutions. Coordinate with focused groups to create unique data infrastructure, run tests on their designs to isolate errors and update systems to accommodate changes in company needs. Responsibilities Assemble large, complex sets of data that meet non-functional and functional business requirements. Identify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes. Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies. Build analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition. Work with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues. Work with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues. Generate or adapt equipment and technology to serve user needs. May perform other job duties as directed by Employee's Leaders Knowledge, Skills and Abilities Knowledge of the practical application of engineering science and technology, including applying principles, techniques, procedures, and equipment to the design and production of various goods and services Knowledge of design techniques, tools, and principles involved in production of precision technical plans, blueprints, drawings, and models. Ability to use logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems. Ability to understand new information for both current and future problem-solving and decision-making. Skilled in identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Ability to tell when something is wrong or is likely to go wrong. It does not involve solving the problem, only recognizing there is a problem. Ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events) Ability to shift back and forth between two or more activities or sources of information (such as speech, sounds, touch, or other sources)

Global Data Center Operators, Are you aware if your hiring process produces genuinely interested candidates or candidates simply looking for a career opportunity in your company? When candidates "want" to work for a data center company, they have a real passion for the industry and the work itself. They may be drawn to the technical aspects of data center management, the fast-paced environment, or the opportunity to work with cutting-edge technology. This kind of motivation can be a powerful driving force in the candidate's career, as it can help them stay engaged and motivated in their work. On the other hand, when a candidate "needs" to work for a data center company, it may be due to external factors, such as financial necessity or a lack of other job opportunities. While this type of motivation can still lead to a successful career in the data center industry, it may provide a different level of fulfillment and engagement than a genuine interest in the work. Therefore, it's essential to make sure your hires have a genuine interest in the industry and the work itself, as they are more likely to find success and fulfillment in your job. Do the more difficult thing. Best, Brian- P.S. Do your employees "want" or "need" to work for you? #datacenters #digitalinfrastructure #interconnection

Hiring Alert‼️ Equifax is hiring for Data Engineers with 2+ years of experience. ✅Direct apply link: https://lnkd.in/d9EwiU-H Stay tuned here Mahesh Gore for more such Data Engineering / Data Analyst related content!! ⚡️Join our telegram community for daily updates, Link in the comments⚡️ #bigdata #dataanalytics #datascience #sql #jobs #interview #jobupdates

What is a data engineer? A data engineer is an IT professional whose primary job is to prepare data for analytical or operational uses. This occupation includes duties such as designing and building systems for collecting, storing and analyzing data. Data engineers are typically responsible for building data pipelines to bring together information from different source systems. These software engineers integrate, consolidate and cleanse data and structure it for use in analytics applications. They strive to make data easily accessible and to optimize their organization's big data ecosystem. The amount of data an engineer works with varies by organization, particularly with respect to its size. The bigger the company, the more complex the analytics architecture and the more data the engineer is responsible for maintaining. Certain industries are more data-intensive, including healthcare, retail and financial services. Data engineers work in conjunction with data science teams, improving data transparency and enabling businesses to make more trustworthy business decisions.