Intro to Spreadsheets, Databases, and Query Languages | Google Data Analytics Certificate

this video is part of the google data analytics certificate providing you with job-ready skills to start or advance your career in data analytics get access to practice exercises quizzes discussion forums job search help and more on casera and you can earn your official certificate visit grow.google datacert to enroll in the full learning experience today [Music] so we've talked a little bit about the data analysis process as a quick refresher the data analysis process phases are ask prepare process analyze share and act you might remember me saying earlier that this entire program is modeled after these steps so now we're going to really dig in and explore how each of these phases work together but i'm getting a little ahead of myself first let's spend a little time understanding the data life cycle no data isn't actually alive but it does have a life cycle so how do data analysts bring data to life well it starts with the right data analysis tool these include spreadsheets databases query languages and visualization software don't worry if you don't know how these work or even what they are at one point every data analyst has been right where you are right now and they probably had a lot of the same questions i remember when i first started learning about spreadsheets i was a young intern and the company i was working for was in the middle of a big systems change that meant we had to move tons of reports from the old system to the new one after a few weeks i noticed that even the people who are further in their careers were not as technically minded as i was so that became a great opportunity for me to add value my aha spreadsheet moment came when i started researching shortcuts that i could use to work with the spreadsheets more efficiently this would really streamline the process of getting those reports moved over to the new system once everything started flowing i remember getting emails from other finance analysts at the company they were so grateful that someone had come in and fixed a problem that no one else could that inspired me to go even further and learn how to use spreadsheets in all sorts of incredible ways as you continue through this course i bet you'll be just as impressed as i was and before you know it you'll bring data to life too let's get started here's a question for you when you think about a life cycle what's the first thing that comes to mind now i'm not a mind reader but i know whatever you're thinking is right there's actually no wrong answer because everything has a life cycle one of the most well-known examples of a life cycle is a butterfly butterflies begin as eggs hatch into caterpillars and then become a chrysalis that's where the real magic happens data has a life cycle of its own too in this video we're going to talk about each of the stages in that life cycle to help you understand the individual phases data goes through the life cycle of data is plan capture manage analyze archive and destroy let's start with the first phase planning this actually happens well before starting an analysis project during planning a business decides what kind of data it needs how it will be managed throughout its life cycle who will be responsible for it and the optimal outcomes for example let's say an electricity provider wanted to gain insights into how to save people energy in the planning phase they might decide to capture information on how much electricity its customers use each year what types of buildings are being powered and what types of devices are being powered inside of them the electricity company would also decide which team members will be responsible for collecting storing and sharing that data all of this happens during planning and it helps set up the rest of the project the next phase is when you capture data this is where data is collected from a variety of different sources and brought into the organization with so much data being created every day the ways to collect it are truly endless one common method is getting data from outside resources for example if you're doing data analysis on weather patterns you'd probably get data from a publicly available data set like the national climatic data center another way to get data is from a company's own documents and files which are usually stored inside a database while we've mentioned databases before we haven't gone into too much detail about what they are a database is a collection of data stored in a computer system in the case of our electricity provider the business would probably measure data usage among its customers within a database that it owns as a quick note when you maintain a database of customer information ensuring data integrity credibility and privacy are all important concerns you'll learn a lot more about that later on now that we've captured our data we move on to the next phase of the data life cycle manage here we're talking about how we care for our data how and where it's stored the tools used to keep it safe and secure and the actions taken to make sure that it's maintained properly this phase is very important to data cleansing which we'll cover later on next it's time to analyze your data this is where data analysts really shine in this phase the data is used to solve problems make great decisions and support business goals for example one of our electricity companies goals might be to find ways to help customers save energy moving on the data lifecycle now evolves to the archive phase archiving means storing data in a place where it's still available but may not be used again during analysis analysts handle huge amounts of data can you imagine if we had to sort through all of the available data that's out there even if it was no longer useful and relevant to our work it makes way more sense to archive it than to keep it around and finally the last step of the data life cycle the destroy phase yes it sounds sad but when you destroy data it won't hurt a bit so let's get back to our electricity provider example they would have data stored on multiple hard drives to destroy it the company would use a secure data erasure software if there were any paper files they would be shredded too this is important for protecting a company's private information as well as private data about its customers and there you have it the data life cycle and now that you understand the different phases data goes through during its life cycle you can better understand how to approach the data analysis process which we'll talk about soon [Music] now that you understand all the phases of the data life cycle it's time to move on to the phases of data analysis they sound similar but are two different things data analysis isn't a life cycle it's the process of analyzing data coming up we'll look at each step of the data analysis process and how it will relate to your work as a data analyst even this program is designed to follow these steps understanding these connections will help guide your own analysis and your work in this program you've already learned that this program is modeled after the stages of the data analysis process this program is split into courses six of which are based upon the steps of data analysis ask prepare process analyze share and act okay let's start with the first step in data analysis the ass phase in this phase we do two things we define the problem to be solved and we make sure that we fully understand stakeholder expectations stakeholders hold a stake in the project they are people who have invested time and resources into a project and are interested in the outcome let's break that down first defining a problem means you look at the current state and identify how it's different from the ideal state usually there's an obstacle we need to get rid of or something wrong that needs to be fixed for instance a sports arena might want to reduce the time fans spend waiting in the ticket line the obstacle is figuring out how to get the customers to their seats more quickly another important part of the ass phase is understanding stakeholder expectations the first step here is to determine who the stakeholders are that may include your manager an executive sponsor or your sales partners there can be lots of stakeholders but what they all have in common is that they help make decisions influence actions and strategies and have specific goals they want to meet they also care about the project and that's why it's so important to understand their expectations for instance if your manager assigns you a data analysis project related to business risk it would be smart to confirm whether they want to include all types of risks that could affect the company or just risks related to weather such as hurricanes and tornadoes communicating with your stakeholders is key in making sure you stay engaged and on track throughout the project so as a data analyst developing strong communication strategies is very important this part of the ask phase helps you keep focused on the problem itself not just its symptoms as you learned earlier the five why's are extremely helpful here in an upcoming course you'll learn how to ask effective questions and define the problem by working with stakeholders you'll also cover strategies that can help you share what you discover in a way that keeps people interested after that we'll move on to the prepare step of the data analysis process this is where data analysts collect and store data they'll use for the upcoming analysis process you'll learn more about the different types of data and how to identify which kinds of data are most useful for solving a particular problem you'll also discover why it's so important that your data and results are objective and unbiased in other words any decisions made from your analysis should always be based on facts and be fair and impartial next is the process step here data analysts find and eliminate any errors and inaccuracies that can get in the way of results this usually means cleaning data transforming it into more useful format combining two or more data sets to make information more complete and removing outliers which are any data points that could skew the information after that you'll learn how to check the data you prepared to make sure it's complete and correct this phase is all about getting the details right so you'll also fix typos inconsistencies or missing in inaccurate data and to top it off you'll gain strategies for verifying and sharing your data cleansing with stakeholders then it's time to analyze analyzing the data you've collected involves using tools to transform and organize that information so that you can draw useful conclusions make predictions and drive informed decision making there are lots of powerful tools data analysts use in their work and in this course you'll learn about two of them spreadsheets and structure query language or sql which is often pronounced sql the next course is based on the share phase here you'll learn how data analysts interpret results and share them with others to help stakeholders make effective data-driven decisions in the share phase visualization is a data analyst's best friend so this course will highlight why visualization is essential to getting others to understand what your data is telling you with the right visuals facts and figures become so much easier to see and complex concepts become easier to understand we'll explore different kinds of visuals and some great data visualization tools you'll also practice your own presentation skills by creating compelling slide shows and learning how to be fully prepared to answer questions then we'll take a break from the data analysis process to show you all of the really cool things you can do with the programming language are you don't need to be familiar with r or programming languages in general just know that r is a popular tool for data manipulation calculation and visualization and for our final data analysis phase we have act this is the exciting moment when the business takes all of the insights you the data analysts have provided and puts them to work in order to solve the original business problem and will be acting on what you've learned throughout this program this is when you'll prepare for your job search and have the chance to complete a case study project it's a great opportunity for you to bring together everything you've worked on throughout this course plus adding a case study to your portfolio helps you stand out from the other candidates when you interview for your first data analyst job now you know the different steps of the data analysis process and how our course reflects it you have everything you need to understand how this course works and my fellow googlers and i will be here to guide you every step of the way i'm looking forward to introducing you to some of the tools data analysts use each and every day there are tons of options out there but the most common ones you'll see analysts use are spreadsheets query languages and visualization tools and this video is going to give you a quick look at how these tools are being used by data analysts every day believe it or not i was several years into my accounting and finance career before i saw all of these tools working together at that point i was very experienced with spreadsheets and had worked in large data sets with some of the traditional database programs i had the foundational skill set to use query languages and i had dabbled in visualizations but i had never brought them all together then i got hired here at google and it was so eye-opening to come into a place like this with an abundance of information everywhere you look as an analyst at google the true power of these tools became so much clearer to me i became more focused on really maximizing everything these tools could do streamlining my reporting and just making my work simpler all of a sudden i had a lot more time and space to dedicate to identifying new problems to solve and driving decision making without a doubt once you've learned the power of these tools you will be well on your way to becoming the best data analyst you can possibly be alright i hope that story has you even more motivated for this course let's get started with spreadsheets again there are lots of different spreadsheet solutions but two popular options are microsoft excel and google sheets to put it simply a spreadsheet is a digital worksheet it stores organizes and sorts data this is important because the usefulness of your data depends on how well it's structured when you put your data into a spreadsheet you can see patterns group informations and easily find the information you need spreadsheets also have some really useful features called formulas and functions a formula is a set of instructions that performs a specific calculation using the data in a spreadsheet formulas can do basic things like add subtract multiply and divide but they don't stop there you can also use formulas to find the average of a number set look up a particular value return the sum of a set of values that meets a particular rule and so much more a function is a preset command that automatically performs a specific process or task using the data in the spreadsheet that sounds pretty technical i know so let's break it down just think of a function as a simpler more efficient way of doing something that would normally take a lot of time in other words functions can help make you more efficient those are the spreadsheet basics for now later on you'll see them in action and start working with spreadsheets yourself the next data analysis tool is called query language a query language is a computer programming language that allows you to retrieve and manipulate data from a database you'll learn something called structured query language more commonly known as sql sql is a language that lets data analysts communicate with a database a database is a collection of data stored in a computer system sql is the most widely used structured query language for a couple of reasons it's easy to understand and works very well with all kinds of databases with sql data analysts can access the data they need by making the query although query means question i like to think of it as more of a request so you're requesting that the database do something for you you can ask it to do a lot of different things such as insert delete select or update data okay that's a top-level look at sql in a later video we'll explore it further and use sql to do some really cool things with data lastly let's talk about data visualization you've learned that data visualization is the graphical representation of information some examples include graphs maps and tables most people process visuals more easily than words alone that's why visualizations are so important they help data analysts communicate their insights to others in an effective and compelling way when you think about the data analysis process after data is prepared processed and analyzed the insights are visualized so it can be understood and shared this makes it easier for stakeholders to draw conclusions make decisions and come up with strategies some popular visualization tools are tableau and looker data analysts like using tableau because it helps them create visuals that are very easy to understand this means that even non-technical users can get the information they need looker is also popular with data analysts because it gives them an easy way to create visuals based on the results of a query with looker you can give stakeholders a complete picture of your work by showing them visualization data and the actual data related to it all visualization tools have great features that are useful in different situations soon you'll learn how to decide which tool to use for a particular job and that's everything you need to know about the data life cycle and the data analysis process you'll get a chance to test out what you know so you can feel confident moving forward in this course feel free to take some time to refamiliarize yourself with the concepts and when you're ready give it your best shot if you're ever unsure of an answer you can always go back and review the videos and readings then you'll be ready to move on to the next set of videos where we'll continue exploring the data analytics tools you've already covered and you'll get some really fascinating insights into exactly how they work before long you'll have the knowledge and confidence to start using them yourself stay tuned congratulations on finishing this video from the google data analytics certificate access the full experience including job search help and start to earn the official certificate by clicking the icon or the link in the description watch the next video in the course by clicking here and subscribe to our channel for more from upcoming google career certificates

Channel: Google Career Certificates

Views: 14,444

Rating: 4.9284115 out of 5

Keywords: Grow with Google, Career Change, Tech jobs, Google Career Certificate, Google Career Certificates, Job skills, Coursera, Certification, Google, professional certificates, professional certificate program, Data analyst, Data analytics, Data analysis, Data analytics for beginners, What is data analytics, Sql, Data, R Programming, Spreadsheets, analyzing data, data integrity, database management system, how to analyze data, data visualization, data analysis in excel

Id: dAyaThLvuug

Length: 20min 41sec (1241 seconds)

Published: Thu Mar 11 2021