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cezarovidiu

8 Principles That Can Make You an Analytics Rock Star -- TDWI -The Data Warehousing Ins... - 0 views

  • Great design, high-quality code, strong business sponsorship, accurate requirements, good project management, and thorough testing are some of the obvious requirements for successful analytics systems.
  • As a professional in the field, you must be able to do these things well because they form the foundation of a good analytics implementation.
  • Successful analytics professionals should follow a set of guiding principles.
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  • Principle #1: Let your passion bloom
  • If you do not love data analytics, it will be hard to become an analytics rock star. No significant accomplishments are achieved without passion. For many people, passion does not come naturally; it must be developed. Cultivate passion by setting goals and achieving them. Realize that the best opportunity in your life is the one in front of you right now. Focus on it, grow it, and develop your passion for it! That excitement will become obvious to those around you.
  • Principle #2: Never stop learning
  • Dig down deeper about the business details of your company. What, exactly, does your company do? What are some of its challenges and opportunities? How would the company benefit from valuable and transformative information you can deliver? Take the time necessary to learn the skills that are valuable for your business and your career. Keep up-to-date with the latest technologies and available analytics tools -- learn and understand their capabilities, functions, and differences.
  • Deepen your knowledge with the tools that you are currently working on by picking new techniques and methodologies that make you a better professional in the field.
  • Principle #3: Improve your presentation skills and become an ambassador for analytics
  • persuasiveness and effectiveness
  • Improve your presentation and speaking skills, even if it is on your own time. Excellent and no-cost presentation training resources are readily available on the internet (for example, at http://www.mindtools.com/page8.html. Practice writing and giving presentations to friends and colleagues that will give you honest feedback. Once you have practiced the basic skills, you need to enhance your skills by improving your
  • You must be able to explain, justify, and "sell" your ideas to colleagues as well as business management. Organizational change does not happen overnight or as a result of one presentation. You need to be persistent and skillful in taking your ideas all the way up the leadership chain.
  • Principle #4: Be the "go-to guy" for tough analytics questions
  • Tough analytics problems typically don't have an obvious answer -- that's why they're tough! Take the initiative by digging deep into those problems without being asked. Throw out all the assumptions made so far and follow logical trial and error methodology. First, develop a thesis about possible contributors to the problem at hand. Second, run the analytics to prove the thesis. Learn from that outcome and start over, if needed, until a significant answer is found. You are now well on your way to rock star status.
cezarovidiu

Why Soft Skills Matter in Data Science - 0 views

  • You cannot accept problems as handed to you in the business environment. Never allow yourself to be the analyst to whom problems are “thrown over the fence.” Engage with the people whose challenges you’re tackling to make sure you’re solving the right problem. Learn the business’s processes and the data that’s generated and saved. Learn how folks are handling the problem now, and what metrics they use (or ignore) to gauge success.
  • Solve the correct, yet often misrepresented, problem. This is something no mathematical model will ever say to you. No mathematical model can ever say, “Hey, good job formulating this optimization model, but I think you should take a step back and change your business a little instead.” And that leads me to my next point: Learn how to communicate.
  • In today’s business environment, it is often unacceptable to be skilled at only one thing. Data scientists are expected to be polyglots who understand math, code, and the plain-speak (or sports analogy-ridden speak . . . ugh) of business. And the only way to get good at speaking to other folks, just like the only way to get good at math, is through practice.
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  • Beware the Three-Headed Geek-Monster: Tools, Performance, and Mathematical Perfection Many things can sabotage the use of analytics within the workplace. Politics and infighting perhaps; a bad experience from a previous “enterprise, business intelligence, cloud dashboard” project; or peers who don’t want their “dark art” optimized or automated for fear that their jobs will become redundant.
  • Not all hurdles are within your control as an analytics professional. But some are. There are three primary ways I see analytics folks sabotage their own work: overly complex modeling, tool obsession, and fixation on performance.
  • In other words, work with the rest of your organization to do better business, not to do data science for its own sake.
  • Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman. Copyright © 2013.
cezarovidiu

Oracle APEX Interactive report based on PLSQL function | Oracle Application Express - 0 views

  • Unfortunately Oracle have failed to allow the report to be based on a PLSQL function returning the query.
  • Step1.Create a collection based on a query. The code for this should be placed in a before header process APEX_COLLECTION.CREATE_COLLECTION_FROM_QUERY(p_collection_name => ‘IR_TEST’,p_query => function_returning_query );
  • Step 2.Create an interactive report querying a collection. Select *From apex_collectionsWhere collection_name = ‘IR_TEST’;
cezarovidiu

Tips and tricks for creating reports - Microsoft Power BI Preview - 0 views

  • When you create a Map, you're often looking to plot Countries, States, and Cities.  If you use name columns after the geographic designation it will help Bing guess what you're looking to display. For example, if you have a field of US state names such as "California" and "Washington", Bing might return the location of Washington, DC instead of Washington State for the word "Washington".  Naming the column "State" will improve the geocoding.  The same is goes for columns named "Country", "State", and "City".  
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