I am not a data scientist or an expert in knowing how to build candlestick charts from historical stock prices. I am however a data enthusiast and it fascinates me when I hear people talk about Big data, like they invented it. Sorry, no offense meant, but really how did we just jump to big data without even creating an understanding about any kind of data?
Information in any shape, form or face is a brilliant resource. We work with information every day and if you look at it, nothing runs without information. Every business of every size, across the world works on information. Yes even the smallest corner store to the corporations working in large glass towers. This information is of many types. Accounting information, sales data, marketing stats, customer information, and purchase order information, patient information, hosting information and so on. Everything we know has some kind of information associated with it. Do we agree so far? Yes we do.
Enter Big data. I often hear people say we have too much data and we have no idea what to do with it. If you are a company like Facebook, Twitter or eBay, you definitely have a lot of data at your hands. For the average company, it is not big data. It is any data. As a small or medium sized company unless you are generating petabytes worth of data from research, or some large scale initiative, you are still in the any data category. When it comes to any data, the question is what are you doing with your data? Have you recently looked at say your customer data and seen if there are any patterns? Have you sifted through your employee data and seen what department provides you with the maximum ROI? I can go on with all sorts of examples. Point is no matter what type of company you are and what size you are, you have access to key data. Your data. This information is invaluable and you cause it to make key decisions for your business today. Here are three data personas that can define your way to work with data and what it can do for you. Perhaps you identify with some of them or may have come across them within your organization. Which one are you?
ANDY THE DATA ARCHER
Any is far too busy with his daily work to bother with working with too much data. He generates a lot of any data, but uses it sparingly during weekly, monthly meetings and so on. Andy is potentially generating a low amount of any data and really does not care what happens to it after, as long as it is available to be retrieved later on. Andy needs data that is sorted, clean and structured to work with. He does not have the skills or time to clean up data. Andy is categorized as a data archer. He uses Data in a precise way to use it for specific needs and to get specific results. He needs data in a ready format (like an arrow) that he can use to get what he wants. Here are some pointers on what does and does not drive Andy.
DO'S: Provide data, discuss data, and discuss how final data can be better suited for his needs
DON'T'S: Work with raw data, provide unstructured or unclean data
EMMA THE DATA ENTHUSIAST
Emma loves data and likes creating insights with any kind of data she can get her hands on. She has an analytical mind and although works in the sales planning department, can work with a lot of data identifying trends, peaks and patterns. Emma needs data to be in a semi clean state when she uses it. Emma knows the impact that data has on her every day job because her work is very much attached to working with it every day. Here are some pointers on what does and does not drive Emma.
DO'S: Get more inside the hood, discuss how data is structured and how it can be better created
DON'T'S: Gets bored with final data, needs to be able to slice and dice, likes getting hands data dirty
WILL THE DATA WORSHIPPER
Will is as analytical as one can get. He has an intricate knowledge of data analysis, techniques and can create candlesticks charts on paper in no time. Will has a deep knowledge of the types of data that can be used for specifically for what purpose. Although not a data analyst like Emma, Will however works with a large team of specialists who help make sense of big data from many databases. Will is driven by unstructured data because he can structure it himself the way he wants. Here are some pointers on what does and does not drive Will.
DO'S: Can work with any data, thrives on large picture yet loves solving complex data problems, idea big data scientist
DON'TS: May get bored with final data use discussions, seeks perfection
All the three personas defined above work with data in one way or the other. Their roles are completely dependent on analyzing data in some way, yet not all of them work with an intricate and massive set of data on an everyday basis. The typical business user today like Andy and Emma know how data works but do not need to get into the structured and unstructured debate, whereas Will thrives on every kind of data. Users like Will who work on specialized pieces of information and massive amounts of information are Big data users.
Meant to be a small insight into our data needs and who out there are driving our data analysis needs, this article is just the tip of the iceberg. Most importantly, keep in perspective that data in any format is key, but it is also important to refer to data in the right way as it impacts a specific end user in the way it is used. What are your thoughts?
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Information in any shape, form or face is a brilliant resource. We work with information every day and if you look at it, nothing runs without information. Every business of every size, across the world works on information. Yes even the smallest corner store to the corporations working in large glass towers. This information is of many types. Accounting information, sales data, marketing stats, customer information, and purchase order information, patient information, hosting information and so on. Everything we know has some kind of information associated with it. Do we agree so far? Yes we do.
Enter Big data. I often hear people say we have too much data and we have no idea what to do with it. If you are a company like Facebook, Twitter or eBay, you definitely have a lot of data at your hands. For the average company, it is not big data. It is any data. As a small or medium sized company unless you are generating petabytes worth of data from research, or some large scale initiative, you are still in the any data category. When it comes to any data, the question is what are you doing with your data? Have you recently looked at say your customer data and seen if there are any patterns? Have you sifted through your employee data and seen what department provides you with the maximum ROI? I can go on with all sorts of examples. Point is no matter what type of company you are and what size you are, you have access to key data. Your data. This information is invaluable and you cause it to make key decisions for your business today. Here are three data personas that can define your way to work with data and what it can do for you. Perhaps you identify with some of them or may have come across them within your organization. Which one are you?
ANDY THE DATA ARCHER
Any is far too busy with his daily work to bother with working with too much data. He generates a lot of any data, but uses it sparingly during weekly, monthly meetings and so on. Andy is potentially generating a low amount of any data and really does not care what happens to it after, as long as it is available to be retrieved later on. Andy needs data that is sorted, clean and structured to work with. He does not have the skills or time to clean up data. Andy is categorized as a data archer. He uses Data in a precise way to use it for specific needs and to get specific results. He needs data in a ready format (like an arrow) that he can use to get what he wants. Here are some pointers on what does and does not drive Andy.
DO'S: Provide data, discuss data, and discuss how final data can be better suited for his needs
DON'T'S: Work with raw data, provide unstructured or unclean data
EMMA THE DATA ENTHUSIAST
Emma loves data and likes creating insights with any kind of data she can get her hands on. She has an analytical mind and although works in the sales planning department, can work with a lot of data identifying trends, peaks and patterns. Emma needs data to be in a semi clean state when she uses it. Emma knows the impact that data has on her every day job because her work is very much attached to working with it every day. Here are some pointers on what does and does not drive Emma.
DO'S: Get more inside the hood, discuss how data is structured and how it can be better created
DON'T'S: Gets bored with final data, needs to be able to slice and dice, likes getting hands data dirty
WILL THE DATA WORSHIPPER
Will is as analytical as one can get. He has an intricate knowledge of data analysis, techniques and can create candlesticks charts on paper in no time. Will has a deep knowledge of the types of data that can be used for specifically for what purpose. Although not a data analyst like Emma, Will however works with a large team of specialists who help make sense of big data from many databases. Will is driven by unstructured data because he can structure it himself the way he wants. Here are some pointers on what does and does not drive Will.
DO'S: Can work with any data, thrives on large picture yet loves solving complex data problems, idea big data scientist
DON'TS: May get bored with final data use discussions, seeks perfection
All the three personas defined above work with data in one way or the other. Their roles are completely dependent on analyzing data in some way, yet not all of them work with an intricate and massive set of data on an everyday basis. The typical business user today like Andy and Emma know how data works but do not need to get into the structured and unstructured debate, whereas Will thrives on every kind of data. Users like Will who work on specialized pieces of information and massive amounts of information are Big data users.
Meant to be a small insight into our data needs and who out there are driving our data analysis needs, this article is just the tip of the iceberg. Most importantly, keep in perspective that data in any format is key, but it is also important to refer to data in the right way as it impacts a specific end user in the way it is used. What are your thoughts?
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