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    How to Analyze a Dataset: 6 Steps

    overhead view of hands pointing at charts and graphs
    • 05 Apr 2017
    HBS Online Author Staff
    tag
    • Analytics
    • Business Analytics

    In the modern world, vast amounts of data are created every day. The World Economic Forum estimates that by 2025, 463 exabytes of data will be created globally every day.

    Rich data can be an incredibly powerful decision-making tool for organizations when harnessed effectively, but it can also be daunting to collect and analyze such large amounts of information.

    Here’s a deeper look at the data analysis process and how to effectively analyze a dataset.

    What Is a Dataset?

    A dataset is a collection of data within a database.

    Typically, datasets take on a tabular format consisting of rows and columns. Each column represents a specific variable, while each row corresponds to a specific value. Some datasets consisting of unstructured data are non-tabular, meaning they don’t fit the traditional row-column format.


    Free E-Book: A Beginner's Guide to Data & Analytics

    Access your free e-book today.

    DOWNLOAD NOW

    What Is Data Analysis?

    Data analysis refers to the process of manipulating raw data to uncover useful insights and draw conclusions. During this process, a data analyst or data scientist will organize, transform, and model a dataset.

    Organizations use data to solve business problems, make informed decisions, and effectively plan for the future. Data analysis ensures that this data is optimized and ready to use.

    Some specific types of data analysis include:

    • Descriptive analysis
    • Diagnostic analysis
    • Predictive analysis
    • Prescriptive analysis

    Regardless of your reason for analyzing data, there are six simple steps that you can follow to make the data analysis process more efficient.

    6 Steps to Analyze a Dataset

    1. Clean Up Your Data

    Data wrangling—also called data cleaning—is the process of uncovering and correcting, or eliminating inaccurate or repeat records from your dataset. During the data wrangling process, you’ll transform the raw data into a more useful format, preparing it for analysis.

    It’s imperative to clean your data before beginning analysis. This is particularly important if you’ll be presenting your findings to business teams who may use the data for decision-making purposes. Teams need to have confidence that they’re acting on a reliable source of information.

    2. Identify the Right Questions

    Once you’ve completed the cleaning process, you may have a lot of questions about your final dataset. There’s so much potential that can be uncovered through analysis.

    Identify the most important questions you hope to answer through your analysis. These questions should be easily measurable and closely related to a specific business problem. If the request for analysis is coming from a business team, ask them to provide explicit details about what they’re hoping to learn, what they expect to learn, and how they’ll use the information. You can use their input to determine which questions take priority in your analysis.

    3. Break Down the Data Into Segments

    It’s often helpful to break down your dataset into smaller, defined groups. Segmenting your data will not only make your analysis more manageable, but also keep it on track.

    For example, if you’re attempting to answer questions about a specific department’s performance, you’ll want to segment your data by department. From there, you’ll be able to glean insights about the group that you’re concerned with and identify any relationships that might exist between each group.

    4. Visualize the Data

    One of the most important parts of data analysis is data visualization, which refers to the process of creating graphical representations of data. Visualizing the data will help you to easily identify any trends or patterns and obvious outliers.

    By creating engaging visuals that represent the data, you’re also able to effectively communicate your findings to key stakeholders who can quickly draw conclusions from the visualizations.

    There’s a variety of data visualization tools you can use to automatically generate visual representations of a dataset, such as Microsoft Excel, Tableau, and Google Charts.

    5. Use the Data to Answer Your Questions

    After cleaning, organizing, transforming, and visualizing your data, revisit the questions you outlined at the beginning of the data analysis process. Interpret your results and determine whether the data helps you answer your original questions.

    If the results are inconclusive, try revisiting a previous step in the analysis process. Maybe your dataset was too large and should have been segmented further, or perhaps there’s a different type of visualization better suited to your data.

    6. Supplement with Qualitative Data

    Finally, as you near the conclusion of your analysis, remember that this dataset is only one piece of the puzzle.

    It’s critical to pair your quantitative findings with qualitative information, which you may capture using questionnaires, interviews, or testimonials. While the dataset has the ability to tell you what’s happening, qualitative information can often help you understand why it’s happening.

    A Beginner's Guide to Data and Analytics | Access Your Free E-Book | Download Now

    The Importance of Data Analysis

    Virtually all business decisions made by organizations are informed by some type of data. Because of this, it’s crucial that businesses are able to leverage data that s available to them.

    Businesses rely on the insights gained from data analysis to guide a myriad of activities, ranging from budgeting to strategy execution. The importance of data analysis for today’s organizations can't be understated.

    Are you interested in improving your data science and analytical skills? Download our Beginner’s Guide to Data & Analytics to discover how you can use data to generate insights and tackle business decisions.

    This post was updated on March 8, 2021. It was originally published on April 5, 2017.

     
    All FAQs

    Top FAQs

    How are HBS Online courses delivered?

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    We offer self-paced programs (with weekly deadlines) on the HBS Online course platform.

    Our platform features short, highly produced videos of HBS faculty and guest business experts, interactive graphs and exercises, cold calls to keep you engaged, and opportunities to contribute to a vibrant online community.

    Are HBS Online programs available in languages other than English?

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    We expect to offer our courses in additional languages in the future but, at this time, HBS Online can only be provided in English.

    All course content is delivered in written English. Closed captioning in English is available for all videos. There are no live interactions during the course that requires the learner to speak English. Coursework must be completed in English.

    Do I need to come to campus to participate in HBS Online programs?

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    No, all of our programs are 100 percent online, and available to participants regardless of their location.

    How do I enroll in a course?

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    Certificate Programs

    HBS Online welcomes committed learners wherever they are—in the world and their careers—irrespective of their professional experience or academic background. To extend the reach of HBS Online, we no longer require an application for our certificate programs. (Applications are still required for our credential programs: CORe and CLIMB.) You can now immediately enroll and start taking the next step in your career.

    All programs require the completion of a brief online enrollment form before payment. If you are new to HBS Online, you will be required to set up an account before enrolling in the program of your choice.

    Our easy online enrollment form is free, and no special documentation is required. All participants must be at least 18 years of age, proficient in English, and committed to learning and engaging with fellow participants throughout the program.

    Updates to your enrollment status will be shown on your account page. HBS Online does not use race, gender, ethnicity, or any protected class as criteria for enrollment for any HBS Online program.

    Credential Programs

    HBS Online's CORe and CLIMB programs require the completion of a brief application. The applications vary slightly, but all ask for some personal background information. You can apply for and enroll in programs here. If you are new to HBS Online, you will be required to set up an account before starting an application for the program of your choice.

    Our easy online application is free, and no special documentation is required. All participants must be at least 18 years of age, proficient in English, and committed to learning and engaging with fellow participants throughout the program.

    Updates to your application and enrollment status will be shown on your account page. We confirm enrollment eligibility within one week of your application for CORe and three weeks for CLIMB. HBS Online does not use race, gender, ethnicity, or any protected class as criteria for admissions for any HBS Online program.

    Does Harvard Business School Online offer an online MBA?

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    No, Harvard Business School Online offers business certificate programs.

    What are my payment options?

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    HBS Online offers a variety of payment methods to provide flexibility, including:

    • Credit and debit cards (Visa, MasterCard, Discover, and AMEX)
    • PayPal
    • Wire transfers
    • Western Union
    • Bank loans (When available)

    You may split your payment across two credit card transactions or send a payment link to another individual to complete payment on your behalf. A minimum payment of $350 is required for the first transaction.

    Some learners may also qualify for scholarships or financial aid, which will be credited against the program fee once eligibility is determined. Please refer to the Payment & Financial Aid page for more information.

    What are the policies for refunds and deferrals?

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    After enrolling in a program, you may request a withdrawal with refund (minus a $100 nonrefundable enrollment fee) up until 24 hours after the start of your program. Please review the Program Policies page for more details on refunds and deferrals. If your employer has contracted with HBS Online for participation in a program, or if you elect to enroll in the undergraduate credit option of the Credential of Readiness (CORe) program, note that policies for these options may differ.

     

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