Petroplan’s Post

Hello ALL! I am currently looking for Data Analyst (Cards & Payments) @ Chicago, IL. Anyone interested? Role: Data Analyst (Cards & Payments)  Location: Chicago, IL Skills recommended: • Strong Business acumen (especially terms level, card product, acquisition/portfolio campaign offers, transactions, reward partner info, rates, fees, Data Analyst duties include: • Perform analysis of tables, understanding their content and relationship to other tables to determine necessary and complete updates • Understand and enforce the data integrity and data governance standards • Translate business requirements into data solutions • Design and support new and existing services or data structures per business requirements • Coordinate change requests • Support the distribution of data and structure changes to multiple copies of the database with minimal productivity interruption. • Turning data into standardized processes / workflows (i.e.: prime rate changes, etc.) • Document processes, procedures, and standards • Account to business partners by including data stewards and business and technology approvers on all changes Skills needed: • Understanding of rule-based logic, business rule engines and workflows • SQL • Analytic mindset • Understanding of normalization vs. denormalization • Relational database structure • Process-oriented • Services knowledge • Problem Solving • Critical thinking #DataAnalyst #SQL #Cards #Payments #Dataintegrity #Datagovernance

When hiring managers are looking for a data analyst, they typically focus on a range of attributes that indicate both technical proficiency and the ability to apply analytical skills in a business context effectively. Here are the top 5 attributes that are often considered important:

When hiring managers are looking for a data analyst, they typically focus on a range of attributes that indicate both technical proficiency and the ability to apply analytical skills in a business context effectively. Here are the top 5 attributes that are often considered important:

What makes you a ‘senior’ data analyst? A) Strong technical skills + Strong domain knowledge B) Expert technical skills + Limited domain knowledge C) Excel + Expert domain knowledge D) None of these -> comment below 👇🏼 There is only one right answer. #Data #Analytics #Recruitment

There are two main types of Data Analyst roles: Type A: Combining Data Analyst and Business Analyst skills. Type B: Combining Data Analyst and Data Engineering skills. Some companies also seek a more comprehensive "Type C" role, which requires a combination of Data Engineer, Data Analyst, and Business Analyst capabilities. The variety in Data Analyst roles reflects the evolving demands of organizations in their data-driven efforts. Therefore, It's essential for companies to clearly define the expectations for each role according to their requirements.

Hi , Every one lets start together , who is a data analyst? A data analyst enables businesses to maximize the value of their data assets through visualization and reporting tools. They're also responsible for profiling, cleaning, and transforming data. Their responsibilities also include designing and building scalable and effective data models, and enabling and implementing the advanced analytics capabilities into reports for analysis. A data analyst works with the pertinent stakeholders to identify appropriate and necessary data and reporting requirements, and then they're tasked with turning raw data into relevant and meaningful insights.

Data Analyst vs. Data Engineer What’s the difference? Imagine building a house 🏡It requires several things: Bricks Wood Windows and more! But someone made sure those materials were delivered and ready for use. They also checked that the materials were of good quality and could bring in more if needed. Likewise, in a company: The Data Analyst builds reports and insights based on: Stakeholder requests Available data Data Engineers make sure the data is available for the analysts. They also ensure the data is clean and can bring in new data sources if required. **Which job do you find more interesting?**👇🏽

If you think you won’t feel this common misconception as an entry level data analyst, think again. As an entry level data analyst, you must feel you not completely prepared to start applying for data analyst role. It is just a common misconception. Here's the thing: it's perfectly normal to feel uncertain. One of the best ways to overcome this is by starting to build a portfolio. Creating projects not only gives you insight into what a data analyst does day-to-day, but it also helps you understand the major aspects of the job. It's never too early to start gaining hands-on experience. As you dive into these projects, you'll identify areas where you lack knowledge. This is important because it directs your learning and helps ensure you're making progress toward your goals. You may never feel 100% ready and that's fine! You don't need to meet all the requirements listed in a job description. If you meet about 50% of them, you're in a solid position to apply. Don't let misconception hold you back; start building your portfolio and take that step forward. P.s what's your thought on building a portfolio?