Spreadsheets are a mainstay in nearly every organization. In fact, they\u2019re often the default, and no one questions their value or whether they\u2019re the right tool for a given job \u2026 or if they\u2019re used simply because they’re available.<\/p>\n
According to the IDC info brief\u00a0“The State of Data Science and Analytics<\/a>,\u201d 88% of data workers, approximately 47 million\u00a0people worldwide, use spreadsheets for data activities.<\/p>\n It\u2019s true that spreadsheets offer value in countless scenarios. With moderately-sized sets of data, spreadsheets are useful for information organization and basic data analysis.<\/p>\n But when the data gets messy or large, spreadsheets quickly become slow and cumbersome to\u202fwork with \u2014 not to mention they’re prone to errors with copying and pasting and rogue formulas.\u202f\u00a0That\u2019s why self-service data analysis is on the rise.<\/p>\n <\/p>\n At its core, self-service data analytics\u00a0places power in the hands of the data professional, whether an entry-level analyst or a data scientist with a statistics background. Platforms that enable modern analytics allow for the ability to democratize\u202faccess to data and provide a playground for data professionals to analyze that data in.\u202fBut don\u2019t worry, IT pros: all that data is still secure and governed.<\/p>\n An end-to-end analytics solution unifies all data professionals in a way that spreadsheets can\u2019t.\u202fRather than having to choose between spreadsheets as a code-free option or learning SQL, R, or Python, self-service data analytics gives you the power of code without the learning curve.<\/p>\n Rather than having to choose between spreadsheets as a code-free option or learning SQL, R, or Python, self-service data analytics gives you the power of code without the learning curve.\u00a0<\/strong><\/p>\n They are the bridge between code-free professionals and coding professionals. So how does that look,\u202fand what are the benefits?\u202f(Don\u2019t worry \u2014 your Excel skills will still come in handy!)<\/p>\n <\/p>\n One of the hallmarks of a self-service data analytics platform is the workflow.<\/p>\n If Excel is known for gridded rows and columns, self-service data analytics platforms are known for their\u202flong-connected\u202fstrings of functions and tools.\u202f\u00a0And that long line \u2014 the common thread from one function to the next \u2014 is a critical factor in building transparency in your team and throughout your organization.<\/p>\n If Excel is known for gridded rows and columns, self-service data analytics platforms are known for their\u202flong-connected\u202fstrings of functions and tools.\u202f\u00a0<\/strong><\/p>\n In Excel, there are a lot of things going on behind the cells. The functions and equations are written up and then disappear\u202fwhen you hit \u201cEnter.\u201d\u202f When you change one number\u202fin one cell, you set off an\u202funseen chain reaction that automatically adjusts the rest of your table. It\u2019s magic, and it’s easy for the magician to keep\u202ftheir process secret, whether they want to keep it secret or not.<\/p>\n Secrecy, of course, is the opposite of understanding and transparency, because when you can\u2019t easily trace your work, it\u2019s easy for mistakes to have a waterfall effect, compounding risk and the effect of human errors.<\/p>\n Secrecy, of course, is the opposite of understanding and transparency, because when you can\u2019t easily trace your work, it\u2019s easy for mistakes to have a waterfall effect, compounding risk and the effect of human errors.<\/strong><\/p>\n With a\u202fworkflow, anyone, including stakeholders without a true analytics background, can understand the basic idea of what is going on in your analysis. That means you can tell a clearer and more compelling story to non-technical people since they can see the workflow right there, threaded across your screen.<\/p>\n On the technical side,\u202fyou can easily share workflows with people across the organization. Not only can your colleagues see what you\u2019ve done, but they can replicate a similar process without reinventing the wheel, or simply build off of your previously created workflow rather than start\u00a0from scratch themselves.<\/p>\n Workflows allow you to see what happened at each stage of the process and easily spot and fix errors without starting over from the beginning.\u202f Basically, they are transparency in action.<\/p>\n <\/p>\n Many analysts spend a large part of their job preparing the same data in the same format. Think\u202fmonthly\u202for quarterly\u202freporting. It\u2019s time-consuming but very important for business functions and happens at regular, predictable cadences.<\/p>\n True, spreadsheets allow\u00a0for some simple automation for basic repetition. But\u202fif you work entirely in Excel,\u202fyou end up doing\u202fthe same tweaking, cleaning, and\u202fwrangling repeatedly.<\/p>\n That\u2019s not the good kind of repeatability. With a workflow in a self-service data analytics environment, since you\u2019ve already built out the logic, you can schedule repeatable workflows to run automatically. If you have quarterly, monthly, or weekly reporting, rather than going through the same tedious\u202fcleaning and\u202fanalysis each time, you can schedule the workflow to pull the necessary data and crunch through everything while you\u2019re asleep.<\/p>\n If you have quarterly, monthly, or weekly reporting, rather than going through the same tedious\u202fcleaning and\u202fanalysis each time, you can schedule the workflow to pull the necessary data and crunch through everything while you\u2019re asleep.\u202f\u00a0<\/strong><\/p>\n Plus, with the right platform, you can turn a workflow into an analytic app that becomes sharable throughout the entire organization. Why make everyone else reinvent the wheel if you already created an awesome workflow? Alternatively, why should you have to reinvent the wheel if a colleague created something valuable that you could use? Remember, good artists borrow, but great artists steal.\u202fIt\u2019s all about reducing tedious tasks, reusing awesome workflows, and recycling valuable processes.<\/p>\n <\/p>\n In the age of Big Data, you need technology and processes that\u202fcan grow with your ever-expanding\u202fdatasets.\u202fFor many data professionals, that\u2019s currently not the case.\u202fThe more data you plug into a spreadsheet, the slower it processes until the dreaded spinning wheel of death appears and the spreadsheet\u202fcrashes your computer or runs out of rows. This is the moment when you question your career, your software choices, and even your sanity. (You know what they say, the definition of insanity is doing the same thing over and over and expecting different results.)<\/p>\n The\u202fself-service\u202fworkflow model allows you to scale and grow your analytics processes way beyond the 1\u00a0million Excel row limit. While the workflows may grow in complexity and scale, their capacity to process enormous sets of data doesn\u2019t diminish \u2014\u202fmost self-service platforms allow you to process data in a separate server so it\u2019s super-fast. Goodbye, spinning wheel of spreadsheet death!<\/p>\n In the age of Big Data, you need technology and processes that\u202fcan grow with your ever-expanding\u202fdatasets.\u202f For many data professionals, that\u2019s currently not the case.\u202f<\/strong><\/p>\n <\/p>\n Although self-service data analytics is a new way of working with and analyzing data, it doesn\u2019t mean that you have to throw out all your\u00a0hard-earned Excel knowledge<\/a>.\u202fThe formats might be different, but much of the analytical logic is the same.<\/p>\n For example, you\u2019re probably pretty good at IF statements in Excel. Great news! You can take that knowledge and easily apply it to a self-service platform. The same goes for many other functions like pivoting data, appending data, and VLOOKUPs. You can perform all those functions in a self-service environment \u2014 but with the self-service take.<\/p>\n Rather than writing out formulas, you drag and drop tools and then reformat within the tools. It\u2019s like taking the best of both worlds \u2014 Excel and workflows \u2014 and having it in one environment.<\/p>\n Seize the day. Explore modern approaches to data analytics that unleash your brilliance. Download \u201cThe Age of the Badass Analyst\u201d to differentiate yourself as the innovative analyst you were meant to be. You\u2019ll learn how to uncover brilliant insights and use the power of advanced analytics \u2014 predictive, prescriptive, and geospatial.<\/p>\nTHE RISE OF SELF-SERVICE DATA ANALYTICS<\/h3>\n
\u00a0THE TRANSITION FROM COLUMNS TO WORKFLOWS<\/h3>\n
REPEATABILITY\u2026 REPEATABILITY<\/h3>\n
SCALABILITY \u2014 GROW WITH BIG DATA<\/h3>\n
TRANSLATE SPREADSHEETS TO SELF-SERVICE<\/h3>\n