Sql Business Intelligence Advancement Workshop – As organizations rely on technology to improve business performance, data literacy is becoming more important than ever. But did you know that having data skills is not a feather in your cap? That’s right, being fluent in the language of data does more than give your organization the ability to deliver impact; It opens you up to a world of new opportunities.
Not surprisingly, there is a growing demand for professionals looking to develop their data skills. If you’re one of them and don’t know where to start, look no further than WeCloudOpen, an accessible learning platform developed by WeCloudData, one of North America’s leading data bootcamps.
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Think of WeCloudOpen as your launching pad into the world of data science. It was designed by a team of data experts and is designed for people who are still on the fence, self-starters or data enthusiasts who are eager to discover their potential. This site gives you access to two great and free offers:
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Although data science involves more than just programming, basic coding skills can make a huge difference in your performance as a data professional. At the top of the list, learning how to code can help you manipulate large datasets, automate repetitive tasks, and improve your problem-solving skills.
WeCloudOpen offers introductory courses to Python and SQL, two of the top coding languages currently used by data professionals.
These courses are self-paced, so you can easily access the recorded videos at your convenience and review the lessons as needed. You can practice your data science skills and knowledge by completing tons of exercises built into the course.
While it usually takes four to six weeks to complete a course, more hours of study can be completed sooner. Once you complete the course, you will receive a certificate that you can share on your LinkedIn.
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But that’s not the best part. It’s this: for $0, you can start building your skills in Python and SQL programming. That’s right – these courses require no financial commitment. So, you get skills, flexibility and credentialing – all without paying a dime!
According to the WeCloudData team, you have a lot to look forward to as Bootcamp launches other self-paced courses on Linux, Machine Learning, Amazon Web Services (AWS) Cloud, Azure Cloud, and Google Cloud.
Data is all around us. And the best part is, if you know how to use it, it’s the key to your career growth! If you want to improve your data skills, look no further than WeCloudOpen.
After mastering the basics of Python and SQL, it’s time to expand your knowledge. If you’re ready for a more in-depth learning experience, WeCloudOpen offers free, accessible workshops in various areas of data science.
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Workshops are held at Zoom for one to two hours, where you can learn directly from data experts. Designed to cover theoretical and practical aspects of the fields, you have the opportunity to update yourself with the latest industry trends, data tools and more. Keynote speakers conduct some sessions to share their experiences and career tips.
Now that you’ve got a proper introduction to the various aspects of data science, it’s time to roll up your sleeves and brush up on your knowledge by exploring WeCloudData’s immersive bootcamp programs.
WeCloudData’s blended interdisciplinary programs are continuously developed with the latest industry requirements in mind, ensuring that you acquire the most relevant skills and knowledge in data. Online programs are offered for part-time and full-time learners to accommodate your needs.
These bootcamps are designed to fully prepare you for data careers by giving you the training and experience to build real-world projects. You will have access to top professionals who will guide and mentor you throughout your chosen program. With WeCloudData’s bootcamps, you can gain the confidence to tackle complex data problems in your future career.
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WeCloudOpen provides a comprehensive gateway to the world of data science. With a variety of free courses and intensive workshops, there’s something to suit everyone’s learning style and areas of interest.
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Rhalyn Claire is a freelance content writer based in Southeast Asia. His years of experience as a marketing professional at several startups and international companies shaped his skills and knowledge, which he now shares through his content. read more
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Before jumping in, understand the scope, long-term, and short-term goals of the solution you’re building. Power BI enables you to generate reports, source and transform data very quickly. But, often at the expense of data governance, data quality and long-term maintenance. Will your first project be a proof of concept or a full-scale production-ready solution? Here are some questions to consider as you go down this path:
Power BI is an incredible self-service reporting tool that can be used to quickly buy and analyze a set of data. Lasting, enterprise-wide solutions require a scalable mindset. For convenience, Power BI Desktop allows one to quickly get from raw data to presentation, but lasting solutions consist of three layers: data transformation, data modeling & data presentation. Query and transformation processes, data models, and report development will be performed and managed by three different people in these specialized roles.
PowerQuery is an amazing data transformation tool that, when used skillfully, offers power and flexibility. Some transformation steps that work with small amounts of data may not work well with large amounts of data sources. Understand your strengths and weaknesses and learn to work with them. Specifically, use parameters, range filters, and how to enable query folding.
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ETL work has always been a discipline of routine and process. Power Query makes this easy but well-designed and manageable transformation queries follow well-defined patterns. After choosing the transformations that work best with your raw data at the right scale, use these guidelines:
Dataflows is the online implementation of Power Query in the Power BI service. Instead of writing queries on the Power BI desktop and storing them in a .pix file, queries can be designed in a web browser and then shared across multiple datasets. There are many good reasons to use Dataflows but they are not a silver-bullet solution for every environment.
A common use for dataflows is to provide a standardized set of transformations and data entities that are not already defined in a central data warehouse. If you already have a data warehouse, some Dataflows functions may be redundant; However they also implement some interesting features such as streaming datasets and AutoML. Start with the basics and learn to use PQ on the desktop, then use Dataflows when needed.
Data modeling power lies at the heart of BI and analytics reporting across the data platform. If you can get the data model right, many things
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