What Is Data Analytics? - An Introduction (Full Guide)

Summary

In the CareerFoundry video, viewers are introduced to the ever-evolving field of data analytics. The video aims to demystify what data analytics entails and its significance in today’s business landscape. By highlighting the process and essential skills needed to become a data analyst, the video provides a comprehensive understanding for beginners. Throughout, it covers the roles and responsibilities of a data analyst, the process of data analysis from defining questions to sharing insights, and the necessary hard and soft skills required for success in this field.

Highlights

• Data analytics helps businesses make smarter decisions by understanding the patterns within raw data. 📈
• A data analyst’s day involves tasks ranging from managing surveys to building and testing code. 🔧
• The data analysis process comprises five main steps: defining questions, collecting data, cleaning data, analyzing, and sharing insights. 🔄

Key Takeaways

• Data analytics is all about extracting useful insights from raw data to drive smart business decisions. 📊
• Being a data analyst involves using various techniques to predict trends, improve efficiency, and make informed decisions. 🔍
• Data analysts require critical skills such as mathematical ability, programming knowledge, and excellent communication skills. 💼

Overview

Data analytics is a buzzword sweeping across businesses right now, but what does it really mean? Essentially, data analytics is the art of studying raw data to extract meaningful insights that can inform business decisions. In its raw state, data doesn’t say much, but data analysts are skilled in piecing together the puzzle to find answers to key business queries.

Within the business world, data analytics is applied in countless ways. From predicting purchasing behaviors and enhancing marketing strategies to boosting operational efficiency, data plays a versatile role. Being able to decipher complex data challenges is crucial for organizations aiming to stay ahead in their industry.

Embarking on a career as a data analyst means equipping yourself with a blend of hard and soft skills. Knowledge in mathematics, familiarity with programming languages like Python and SQL, and a knack for problem-solving are just the start. Moreover, as a data analyst, strong communication skills are vital to present findings clearly to stakeholders and to help guide the company's strategy.

Chapters

• 00:00 - 00:30: Introduction to Data Analytics The chapter begins by introducing the concept of data analytics, highlighting its burgeoning significance in the business sector. It emphasizes the transformative power of data analytics and aims to provide a foundational understanding of what being a data analyst entails. By the end of the chapter, readers should have clarity on the nature of data analytics and the primary responsibilities involved in the field. The chapter sets the stage to delve into five key aspects that define the role and pathway to becoming a data analyst.
• 00:30 - 01:00: The Role of a Data Analyst This chapter introduces the role of a data analyst, highlighting that most companies collect vast amounts of data that, in its raw form, is not very useful. The chapter emphasizes that the purpose of data analytics is to analyze this raw data to unlock its true value.
• 01:00 - 01:30: Importance of Data Analytics In this chapter on the Importance of Data Analytics, it is emphasized how vital data insights are for companies. Data analytics drives smart business decisions by turning complex jigsaw-like data into comprehensible and actionable insights. This process is akin to business intelligence, aiding companies in solving problems and challenges through detecting useful patterns within the data.
• 01:30 - 03:00: How Data Analytics is Used The chapter "How Data Analytics is Used" discusses the practical applications of data analytics in business operations. It explores how insights from data help companies make informed decisions about their audience, company, and industry. The chapter follows a structure where the first step revisits what Data Analytics is, while the second step delves into its real-world usage, illustrating examples of how both customer and employee engagements with products and tools are analyzed to optimize business strategies.
• 03:00 - 04:00: Day-to-Day Tasks of a Data Analyst The chapter discusses the ubiquitous nature of data in the real world and its numerous applications across various businesses and organizations globally. It highlights the primary uses of data analytics, which include making faster and better business decisions, reducing overall business costs, and developing new and innovative products and services. Specific applications of data analytics are also discussed such as predicting future sales or purchasing behaviors, enhancing security to prevent fraud, and analyzing the effectiveness of marketing campaigns.
• 04:00 - 07:00: The Data Analysis Process The chapter titled "The Data Analysis Process" begins with an overview of practical applications of data analytics, such as enhancing customer acquisition and retention, as well as increasing supply chain efficiency. The transcript then transitions into exploring the daily activities and responsibilities of a data analyst. This includes providing insights based on real job descriptions, which may be useful for individuals considering a career in data analysis.
• 07:00 - 09:00: Skills Needed to Become a Data Analyst This chapter covers the skills necessary to become a data analyst. Key responsibilities include managing user satisfaction surveys, reporting results using data visualization software, collaborating with business line owners to develop requirements, defining success metrics, and managing analytical projects. Data analysts must also monitor practices and processes to identify improvement opportunities and translate questions into analytical tasks. Additional tasks involve gathering new data, organizing data from multiple sources, and maintaining back-end code.
• 09:00 - 10:00: Conclusion and Further Resources The conclusion chapter summarizes the role of a data analyst in establishing data processes, defining data quality criteria, and implementing necessary processes. It emphasizes the importance of teamwork in evaluating key data to shape future business strategies. The chapter advises readers interested in the field to explore job boards like LinkedIn, Indeed, and icrunchdata.com for a broad overview of a data analyst's responsibilities.

What Is Data Analytics? - An Introduction (Full Guide) Transcription

• 00:00 - 00:30 Data Analytics everyone's talking about it but  what exactly is it perhaps you've heard that Data   Analytics is the next big thing for business  and want to find more about what the field   involves by the end of this video you should have  a better understanding of what data analytics is   and you'll have a better understanding  of what you'll be doing in the role in this video we're going to cover five key points  to give you a better understanding of what it is   to be a Data Analyst and how do you start working  in this field as you're watching the video if   you've got any questions about the topics that we  cover just drop them in the comments below before
• 00:30 - 01:00 we dive in if you're enjoying the video content  please give us a like and subscribe to get more   weekly videos like this so let's dive into step  number one perhaps you're thinking about becoming   a data analyst and want to know exactly what a  career in the field involves most companies are   collecting loads of data all the time but in its  raw form this data doesn't actually mean anything   this is where data analytics comes in data  analytics is the process of analyzing raw data
• 01:00 - 01:30 so that we can pull out insights which are useful  to companies these insights are super important to   drive smart business decisions what a data analyst  does is they take all this complex jigsaw of data   they take it out and they make it into  something which you can really use   having interpreted the data the data analyst can  then pass these insights on so that the company   can then make the most informed decisions  so you can think of data analytics as a   kind of business intelligence used to solve  problems and challenges that every company has   it's all about finding patterns in the data which  can tell you something useful or relevant about
• 01:30 - 02:00 the business operations so for instance how  customers engage with a particular product or   employees engage with a particular tool armed with  the insights of data companies are then able to   make better decisions about their audience company  as a whole and the industry in which they work in Step one we looked at what Data Analytics  actually is in step two we're going to look   at how data analytics is used so what does data  analytics actually look like in action and how is
• 02:00 - 02:30 it used in the real world so the fact is data is  everywhere so it actually has an infinite amount   of uses across all kinds of businesses and  organizations globally broadly speaking data   analytics is used to make faster and better  business decisions to reduce overall business   costs and to develop new and innovative products  and services in more specific terms data analytics   might be used to do the following to predict  future sales or purchasing behaviors for security   purposes to help and protect against fraud to  analyze the effectiveness of marketing campaigns
• 02:30 - 03:00 to boost customer acquisition and retention or  to increase supply chain efficiency so that gives   you a little bit of an overview of what data  analytics can be used for in the real world Step three let's dive into what a data  analyst actually does on a day-to-day basis   if you're thinking about becoming a data analyst  you're probably interested in the roles and   responsibilities that you'll have in the field  based on some real job ads here are some typical
• 03:00 - 03:30 roles and responsibilities that you'll have to  undertake as a data analyst manage the delivery   of user satisfaction surveys and report on  results using data visualization software   work with business line owners to develop  requirements define success metrics   manage and execute analytical projects and  evaluate results monitor practices processes   and systems to identify opportunities for  improvement translate important questions   into concrete analytical tasks gather new  data to answer client questions collating   and organizing data from multiple sources  design build test and maintain back-end code
• 03:30 - 04:00 establish data processes define data quality  criteria and implement data quality processes   work as part of a team to evaluate and analyze key  data that will be used to shape future business   strategies so those are just some examples of what  a data analyst would be doing in any given role   to learn more about the kinds of things that  you'll be undertaking as a data analyst why   not search on job boards like linkedin indeed  and icrunchdata.com so that was step three   it was just a broad overview of what you  can expect to be doing as a data analyst
• 04:00 - 04:30 So now we've looked at data analytics as a role  we're now going to go into the process of data   analysis so now we're going to outline  the five main steps a data analyst would   take when approaching a new project step one  define the questions that you want to answer   you need to answer why you're conducting this  analysis and what questions and answers you   need to find at this stage you'll take a clearly  defined problem and then you'll make a hypothesis
• 04:30 - 05:00 or research question that you can go on and  answer you'll then need to identify what types   of data you'll need but importantly where it  will come from for instance a business problem   might be that customers aren't subscribing to  a paid membership once that free trial ends   your key question can then be what kind  of strategies can the business implement   to retain their customer base step two would be  to collect this data with a clear question in mind   you're ready to start collecting that data data  analysts will usually gather data from primary   sources or internal data that the company already  has such as CRM software or email marketing tools
• 05:00 - 05:30 they may tend to secondary or external sources  such as open data sources so this can include   data from government portals tools like  google trends but also data from international   organizations like the world health organization  so step three you need to clean scrub that data   once you've got that data you need to prepare  it and ready it for analysis your original data   might include duplicates anomalies or missing data  which could distort how the data is interpreted
• 05:30 - 06:00 these all need to be removed data cleaning can be  a manual task and it can take some time but it's   crucial if you want to get the right business  insights step four is to analyze the data now   for the actual analysis how you analyze the data  will depend on the question that you're asking   and the kind of data that you're working  with but some common techniques include   regression analysis cluster analysis and time  series analysis to name just a few we're going to   go into these analysis terms much deeper in future  videos but if you have any specific questions now
• 06:00 - 06:30 drop us a comment in the comments below moving  on to step 5 we need to interpret and share the   results the final step in this process is where  data is turned into valuable business insights   depending on the type of analysis conducted you'll  present your findings in a way that others can   understand in the form of a chart or a graph for  example at this stage you'll be able to say what   the data analysis actually shows you in regards  to your initial question or business challenge   and you'll collaborate with key stakeholders  on how to move forward this is a great moment
• 06:30 - 07:00 to reflect and look at the limitations of your  data and what further analysis might be conducted   rounding off step four we're going to move  on to the next step what skills you need   to actually become a data analyst in addition to  the role description and the processes that we've   described so far data analysts are also expected  to demonstrate certain skills and abilities   here are some of the most important hard and soft  skills that you'll need to become a data analyst   you'll need to have some mathematical and  statistical ability data analysts spend a lot
• 07:00 - 07:30 of their time crunching numbers so you'll need to  have a mathematical brain you'll have to have some   working knowledge of programming languages such  as python oracle and sql data analysts rely on   a number of programming languages to carry out  their work this may seem daunting at first but   it's nothing that can't be learned over time with  practice you'll also need an analytical mindset   it's not just about crunching the numbers and  sharing your data sometimes you'll need to dig   deeper to understand really what's going on  it's all in the name an analytical mindset is
• 07:30 - 08:00 a must remember data analytics is about answering  questions and solving business challenges and that   requires some keen problem-solving skills data  analysts have a wide variety of tools at their   disposal and you'll need to know which one to use  and when you'll also need excellent communication   skills once you've harvested your data for  valuable insights it's important to share your   findings so that it benefits the business data  analysts work in close collaboration with key   business stakeholders and they may be responsible  for sharing their insights to those stakeholders
• 08:00 - 08:30 but also the entire company so if you're thinking  about becoming a data analyst you need to be   comfortable with this aspect of the job so that  summarises some of the key hard and soft skills   you'll require as a data analyst i hope this  has been a value obviously this isn't a broad   overview of the field at hand if you've enjoyed  this video we've got an in-depth article covering   the points which i've mentioned in the video  and we go into much greater depth the link for   that is in the description below career foundry  also have a fantastic five-day data analytics   short course so if you're interested just sign  up in the description below if you've got any
• 08:30 - 09:00 questions about the field or the topics that we've  covered in this video please just drop them in the   comments below thank you so much for watching and  we'll see you again soon okay cuts or anonymous some typical job ads ads check out those apps   so what data analyses ulysses  data analyst analyssssis data set