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Data Analytics Google Module 1 Data is a collection of facts. This collection can include numbers, pictures, videos, words, measurements, observations, and more. Data Analysis is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making. People analytics is the practice of collecting and analyzing data on the people who make up a company's workforce in order to gain insights to improve how the company operates.involves using data analysis to gain insights about employees and how they experience their work lives. The insights are used to define and create a more productive and empowering workplace. This can unlock employee potential, motivate people to perform at their best, and ensure a fair and inclusive company culture. six steps of the data analysis process Ask, Prepare, Process, Analyze, Share, Act Ask you'll work to understand the challenge to be solved or the question to be answered. It will likely be assigned to you by stakeholders. As this is the ask phase, you'll ask many questions to help you along the way. Prepare you'll find and collect the data you'll need to answer your questions. You'll identify data sources, gather data, and verify that it is accurate and useful for answering your questions. Analyze is when you do the necessary data analysis to uncover answers and solutions. Depending on the situation and the data, this could involve tasks such as calculating averages or counting items in categories so you can examine trends and patterns. Share when you present your findings to decision-makers through a report, presentation, or data visualizations. As part of the share phase, you decide which medium you want to use to share your findings and select the data to include. Tools for presenting data visually include charts made in Google Sheets, Tableau, and R. Act phase
in which you and others in the company put the data insights into action. This could mean implementing a new business strategy, making changes to a website, or any other action that solves the initial problem. EMC's data analysis process EMC Corporation's data analytics process is cyclical with six steps: Discovery Pre-processing data Model planning Model building Communicate results Operationalize EMC Corporation is now Dell EMC. This model, created by David Dietrich, reflects the cyclical nature of typical business projects. The phases aren't static milestones; each step connects and leads to the next, and eventually repeats. Key questions help analysts test whether they have accomplished enough to move forward and ensure that teams have spent enough time on each of the phases and don't start modeling before the data is ready. It is a little different from the data analysis process on which this program is based on, but it has some core ideas in common: the first phase is interested in discovering and asking questions; data has to be prepared before it can be analyzed and used; and then findings should be shared and acted on. SAS's iterative process An iterative data analysis process was created by a company called SAS, a leading data analytics solutions provider. It can be used to produce repeatable, reliable, and predictive results: Ask Prepare Explore Model Implement Act Evaluate The SAS model emphasizes the cyclical nature of their model by visualizing it as an infinity symbol. Its process has seven steps, many of which mirror the other models, like ask, prepare, model, and act. But
have just broken down what has been referred to as prepare and process into smaller steps. It emphasizes the individual tasks required for gathering, preparing, and cleaning data before the analysis phase. Ecosystems a group of elements that interact with one another. Ecosystems can be large, like the jungle in a tropical rainforest or the Australian outback. Or, tiny, like tadpoles in a puddle, or bacteria on your skin. And just like the kangaroos and koala bears in the Australian outback, data lives inside its own ecosystem too. data ecosystems are made up of various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data. the cloud is a place to keep data online, rather than on a computer hard drive. So instead of storing data somewhere inside your organization's network, that data is accessed over the internet. Data Science vs. Data Analytics Data scientists create new questions using data, while analysts find answers to existing questions by creating insights from data sources. There are also many words and. phrases you'll hear throughout this course, that are easy to get mixed up. For example, data analysis and data analytics sound the same, but they're actually very different things. Let's start with analysis. You've already learned that data analysis is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making. Data analytics in the simplest terms is the science of data. It's a very broad concept that encompasses everything from the job of managing and using data to the tools and methods that data workers use each and every day. So when you think about data, data analysis and the data ecosystem, it's important to understand that all of these things fit under the data analytics umbrella. data analytics the science of data data science is defined as creating new ways of modeling and understanding the unknown by using raw data.
Data-driven decision making Using facts to guide business strategy subject matter experts they have the ability to look at the results of data analysis and identify any inconsistencies, make sense of gray areas, and eventually validate choices being madeSources such as supervisors and incumbents who are knowledgeable about a job. Analytical skills Qualities and characteristics associated with using facts to solve problems Technical mindset The analytical skill that involves breaking processes down into smaller steps and working with them in an orderly, logical way. For instance, when paying your bills, you probably already break down the process into smaller steps. Maybe you start by sorting them by the date they're due. Next, you might add them up and compare that amount to the balance in your bank account. This would help you see if you can pay your bills now, or if you should wait until the next paycheck. Finally, you'd pay them. When you take something that seems like a single task, like paying your bills, and break it into smaller steps with an orderly process Data design The analytical skill that involves how you organize information Data strategy The analytical skill that involvesThe management of the people, processes, and tools used in data analysis. Let's break that down. You manage people by making sure they know how to use the right data to find solutions to the problem you're working on. For processes, it's about making sure the path to that solution is clear and accessible.
