Blueprint Test Prep’s Post

Why I Love Recruiting in Business Intelligence and Analytics Engineering Business Intelligence is the backbone of any data-driven business, and the field is continuously evolving. Every company seeks to innovate, whether it’s optimizing visualizations, enhancing data warehousing, refining ETLs, adopting modern self-serve analytics, integrating advanced transformation tools, or undergoing a complete platform overhaul. There’s always something exciting happening! Are you looking to grow your BI and Analytics team? Let’s connect! Drop me a message, and let’s explore how we can achieve your goals together. #businessintelligence #analyticsengineering #datahiring

Big Data Analytics: Shaping the Future, Not Just Reflecting the Past. 📊🚀 In the age of data-driven decision-making, Big Data Analytics is the compass guiding us toward a future filled with insights and innovation. It's not just about looking back; it's about forging ahead. #BigDataAnalytics #FutureInsights #Innovation #ContractStaffing #WorkforceFlexibility #EndurtechAdvantage #WorkforceSolutions #Flexibility #Expertise #Jobs #Hiring #JobSearch #Recruiting #Recruiter #Technology #FlexibleStaffing #Staffing #StrategicWorkforce

𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐭𝐡𝐞 𝐃𝐫𝐞𝐚𝐦 𝐓𝐞𝐚𝐦: 𝐇𝐢𝐫𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥𝐬 𝐟𝐨𝐫 𝐓𝐨𝐝𝐚𝐲'𝐬 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 𝐓𝐞𝐚𝐦 Assembling the right data team is crucial for organizations striving to derive actionable insights and stay competitive. The evolving landscape demands professionals with a diverse skill set and the ability to navigate complex datasets. Let's outline key qualities and skill sets to look for when hiring data professionals for today's modern data team. 👥Analytical Skills 👥Technical Proficiency 👥Data Management and Governance 👥Domain Knowledge 👥Communication Skills 👥Problem-Solving Abilities 👥Curiosity and Continuous Learning 👥Team Collaboration 👥Ethical Considerations 👥Diversity and Inclusion 𝑪𝒐𝒎𝒑𝒍𝒆𝒕𝒆 𝒂𝒓𝒕𝒊𝒄𝒍𝒆: https://lnkd.in/gRr_jDUm If your organization needs help building a data dream team, reach out for a 𝐅𝐑𝐄𝐄 1 hour strategy session here: https://lnkd.in/gSqv7sTk. Leave the conversation with 3, or more, actionable insights to improve your data program today! If you enjoy this content please engage with and/or comment on the post, repost to your network AND follow Fox Consulting by clicking on the 🔔 on the profile to get a notification for all new posts! Subscribe to my weekly newsletter and NEVER miss any of the haute data tips (or memes): https://lnkd.in/gPH_BR7F New articles are released each Friday and can ONLY be found in the Newsletter first! #businessintelligence #dataanalytics #datasecurity #datagovernance #datastrategy #datainitiatives #datawarehouse #datamanagement #testautomation #dataquality

Data-driven decision-making is the future of business. As data analysts, we're shaping this future by transforming raw data into actionable insights. Together, we're driving innovation and creating a data-powered world! Let's raise our glasses to the power of data! 🚀📈 #datadrivenfuture #innovation #datareflections #dataappreciation #dataanalystlife #datainsights #datavisualization #datastorytelling #datadriveninsights #datatips #dataanalysis #datadrivendecisions #intelligentanalytics #datavisualization #interactivereports #powerbiexcel #dataanalysis #dataintegration #datastorytelling #datacommunication #powerquery  #datadrivendecisions #businessinsights  #dataanalytics #learningjourney #microsoft #linkedin #linkedinnetwork #linkdinpost #linkdinfamily #linkedinlearning #linkedincommunity #linkedinconnections

🚀 𝐃𝐄 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰📢 𝐒𝐩𝐚𝐫𝐤 ⌛ 𝟏-𝐌𝐢𝐧-𝐑𝐞𝐚𝐝 "𝐏𝐚𝐢𝐫 𝐑𝐃𝐃 𝐯𝐬 𝐌𝐚𝐩 𝐢𝐧 𝐒𝐩𝐚𝐫𝐤" 🔍 🧔🏽♂️ Interviewer: Can you explain the difference between Pair RDD and Map in Spark and what happens if they don't exist? 👨🦰 Interviewee: Pair RDDs and Maps play different roles in Spark. Pair RDDs represent key-value pairs, while Maps are collections that store key-value pairs. Pair RDDs are particularly useful for operations like aggregations and joins, where data needs to be grouped by keys. If Pair RDDs or Maps don't exist, performing key-based operations efficiently becomes challenging, leading to potential performance bottlenecks and increased complexity in data processing. 🧔🏽♂️ Interviewer: Can you elaborate on the implications of not having Pair RDDs or Maps in Spark? 👨🦰 Interviewee: Without Pair RDDs or Maps, tasks such as grouping data by keys or performing key-based transformations would require manual handling and custom implementations, which can be time-consuming and error-prone. Additionally, the absence of these abstractions may lead to less efficient data processing and hinder scalability, especially in scenarios involving large datasets and complex transformations. 🧔🏽♂️ Interviewer: How do they contribute to performance optimization? 👨🦰 Interviewee: Pair RDDs and Maps enable efficient key-based operations, such as aggregations, joins, and transformations, by providing built-in abstractions and optimizations. Pair RDDs, for example, leverage partitioning and shuffle optimizations to enhance performance during key-based operations, while Maps offer fast key lookup and retrieval, improving overall processing speed and resource utilization. 🧔🏽♂️ Interviewer: What strategies would you recommend for maximizing their effectiveness? 👨🦰 Interviewee: To maximize the effectiveness of Pair RDDs and Maps, it's essential to design data pipelines and transformations that leverage their strengths efficiently. This includes choosing appropriate data structures, partitioning strategies, and optimization techniques tailored to the specific requirements of the data processing tasks. #OneStepAnalytics #DataAnalytics #BigData #SQL #DataProcessing #DataWarehouse #DataEngineering #DistributedComputing

⚠ A primary challenge of analytics: Counting ⚠   📝 You will spend an inordinate amount of time counting things.   I don't just mean 1,2,3,4.   We can all do that simple counting..   Sometimes we need to count DISTINCT. Well, heck, that raises a whole other host of issues. ❓ Do we have a distinct identifier? ❓ Can we combine fields for a distinct count? ❓ Is the data clean enough for use to get a true count?   ⚠ But then there are additional issues, mostly revolving around HOW to count something: ❓ Can we join this to something else that has the classifier? ❓ Do variants of this product count as their own product? ❓ What constitutes a continuing customer? Lost customer? Returning customer? ❓ Which medical codes do we include in this event? (that can launch of LOT of analysis and debate) ❓ When do we count something as "late"? ❓ Who is a diverse hire? ❓ Which sales leads do we count to calculate our conversion rate (← my most dreaded question of all time 😱)   How much of analytics is? ◼ Grouping stuff into buckets so we can COUNT members of those buckets. ◼ Defining a relationship, so we can COUNT the entities with that relationship.   Maybe I am just saying that it all comes down to counting?   ✍ tell me in the comments about something you have struggled to count.   🏗→🧠 Build to Learn!   💭🚶♀️🚶♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

RECRUITER: How do you know that you have done #Datamodelling right? me: Well in simple terms #datamodelling would be defined as simply be a way of representing,organizing and structuring data to meet specific business needs. well how do you organize your data as a data engineer? How do you make it available for your team? It ain't about being fancy ,it has to have the business aspect(domain) and knowledge behind it and how fast do you retrieve and make queries? And it goes without asking which schema do you choose #starschema. or the #snowflakeschema? There are three main approaches to #datamodelling 1.conceptual modelling - identifies core entities and relationships within data domain focusing, and understanding business concepts. 2.Logical modeling -defines the logical structure of data including data types, constraints and relationships 2.Physical modelling - translates logical modeling into specific implementation details into a database At the end of making all these business decisions based on what data you really require for your business then you move on to create an #entityrelationshipdiagram this is a diagram that contains all the tables and the data columns in tables with some columns been foreign keys of other columns in other tables And now here is the answer to your question A very simple hack to this is using #powerbi and when you load the data to power bi and view the model view tab the relationship will be well detailed and visible detailing the relationships that you have set between the tables and also the kind of relationship,if this does not happen when you view the model tab then something has not been done right We will look at #databasenormalization next #dataengineering #datascience #machinelearning

🚀 Exciting times in the data domain job market! As we gear up for more opportunities, let's dive into a famous SQL interview question that might just pop up. Question: How to fetch unique values from a table without using the DISTINCT keyword? Table Creation Script: CREATE TABLE Employee ( ID INT, EmployeeName VARCHAR(50), Department VARCHAR(50) ); INSERT INTO Employee VALUES (1, 'Alice', 'IT'), (2, 'Bob', 'Finance'), (3, 'Charlie', 'IT'), (4, 'David', 'HR'), (3, 'Charlie', 'IT'), (1, 'Alice', 'IT'); Now, let's explore couple of ways to tackle this challenge: 1. Using GROUP BY: SELECT ID,EmployeeName, Department FROM Employee GROUP BY ID,EmployeeName, Department 2. Using ROW_NUMBER(): WITH RankedEmployees AS ( SELECT EmployeeName, ROW_NUMBER() OVER (PARTITION BY EmployeeName ORDER BY ID) AS RowNum FROM Employee ) SELECT EmployeeName FROM RankedEmployees WHERE RowNum = 1 Feel free to share your thoughts and alternative solutions. Let's keep the conversation flowing! 💬🔗 #DataJobs #SQLInterview #TechTalk

For more senior data roles, you’ll frequently get asked this type of question: “How would you go about optimizing this query?” It’s a pretty open ended question, with lots of potential answers. Here are my suggestions for how you can answer: 1️⃣ Add an index to your tables. Indexes help queries find the appropriate row, making query performance quite quicker. 2️⃣ Rewrite your query. If your query has a large number of subqueries or CTEs trying combining them. If your query had none, try using a CTE. 3️⃣ Check your joins. Are you left joining when you could be inner joining? Can you join on more than one field? Try isolating which join is slowing down your query. 4️⃣ Tell the interviewer you would consult the query execution plan. In some IDEs the execution plan will tell you where the bottlenecks in your query are. How do you answer this question when interviewing? #datawithdickson #dataengineering #dataanalytics

𝗗𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗶𝘀 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗶𝘀 𝗡𝗢𝗪! Join the most demanding 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲 𝗼𝗻 "𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗘𝘅𝗰𝗲𝗹, 𝗚𝗼𝗼𝗴𝗹𝗲 𝗦𝗵𝗲𝗲𝘁𝘀, 𝗮𝗻𝗱 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜" and ready yourself for this job market. Data analysts are among the most in-demand professionals in the world. Because the demand is so high and the supply of people who can truly do this job well is so limited. 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗦𝘁𝗮𝗿𝘁𝘀: August 25, 2023 𝗟𝗮𝘀𝘁 𝗗𝗮𝘁𝗲 𝗼𝗳 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: August 17, 2023 𝗖𝗹𝗮𝘀𝘀 𝗧𝗶𝗺𝗲: Every Thursday and Friday (8:00 PM - 9:30 PM) 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗟𝗶𝗻𝗸: https://lnkd.in/eFEriJsk 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 𝗨𝘀: 01894 – 627100, 01894 – 627101 #DataAnalyticsMastery #UnlockingDataInsights #AnalyticsForSuccess #DataDrivenDecisions #DataAnalyticsProfessionals #DataVisualizationExperts #DataDrivenStrategy #AnalyticsCertification #DataScienceSkills #MasteringDataAnalysis