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Difference Between Business Analyst And Data Analyst

Difference Between Business Analyst And Data Analyst

Business analysis and data analysis are some of the most vital things that are driving the world of data and business today right these two are among the top 10 carriers for this particular ticket and it’s been forecast for the next decade as well we are just starting out this decade and it just shows how powerful.

How effective these two job roles are now I’m sure you guys are very curious about what a business analyst does and of course what a data analyst does and how they compare to each other what are the similarities what are the differences primarily and a lot more right so keeping that in mind we here in Delhi part have come up with this business analyst versus data analyst video which will give you a lot of insight and in-depth comparison.

Business analyst versus data analyst video let’s take a quick introduction to understand what business analysis is seen business analysis is a process of how one can go on to pick up a lot of data from multiple places you know run visualizations on it perform some analysis on it in a way where this analysis can be used the result can be used to actually go on to drive a business decision.

For example, there might be so many things that might be affecting the sales of a product in the region right so the requirement may be for you know less female running shoes or you know smaller size shoes in that particular region you might be stocking up a lot on you know male running shoes or maybe a bigger size that you’re talking that you’re stocking at now in that particular case what the requirement asks is to make sure that you match the customer demand,

What you are providing to that is one very good example of what business analytics is and then you know to bridge this kind of a talk with the data that we’re providing.

Data is the foundational aspect of what business analysis is to perform an analysis and to drive a business informed decision based on that you’re going to require a lot of data because more the data better the analysis,

The data we generate every day we generate 2.5 quintillion bytes of data every day that’s uh you know so if you’re wondering how much 2.5 quintillion is one quintillion is 1000 quadrillion bytes one quartile is 1 000 trillion and 1 trillion is 1 000 billion and I’m sure you know you know how much the entire data that we have in today’s world 90 of it was generated right under our nose in the last three years itself.

When you think about it we are generating much data and when you make good use of this data you can have amazing analytics to use that past and present data to forecast something that might happen in the future too now you know this is something that the world is dumping on the world understands the value of data.

There’s a code that says data is the new oil and I definitely think that adds a lot of value here what does a business analyst, business analyst has the capability of ingesting data be it clean data or messy data, and converting it into two things.

The end result of what a business analyst does is either pick up business insights from the data that was given to him or her and of course, you know there’s going to be a certain byproduct which we call noise.

Data there are two types of data one we have the clean data it can be structured semi-structured even unstructured data can be considered clean in a way where analyzing that will make sure that your business analyst’s decision does not get affected because of a fault in the data now with messy data.

There can be chances where your data can be misleading and it can affect the accuracy of a certain detection it can affect the accuracy of what insights can be driven and it can definitely turn the ship around we don’t want that in practical situations it is extremely hard to filter through and clean data in a in a to a point where it’s 100 clean this is where data pre-processing comes into the pictures,

Data engineers are the people responsible for ingesting the data and cleaning them up and then driving the business inside aspect of things is everything that we look forward to and of course when you are gone to have information in this particular case sometimes ninety percent of it is something which is very useful ten percent of it is not going to be of use.

That’s a fair game you can avoid and chuck the ten percent to make sure that you pull your attention and efforts into the ninety percent too now with that you have to understand what data analysis is I’m sure if you’re at this article you have a certain clue or certain sense,

what data analysis is well data analysis is one of the most important roles that is required in today’s world because here what we try to do is we create we visualize and we tell stories with data this is done to make sure we can have better business decisions across you know across the spectrum of working now if you’re wondering this sounds similar to what a business analyst does well let me tell you it is quite similar.

it is hugely different in a way too because here what a data analyst does is he or she is responsible for the data system design and development a lot of skills are required in terms of data mining data preparation data cleaning and data ingestion of course and at the end of the day to tell a story better what better way can you put it out than creating beautiful dashboards reports and visualizations.

That is one of the most important things a data analyst does he or she will have the complete knowledge of how to work with data how to everything from ingestion all the way to processing it driving insights out of it visualizing it conveying it to stakeholders,

The entire end-to-end thing which includes a lot of technical skills and non-technical skills is something a data analyst should have in his or her domain and then coming to the comparison itself in between a business analyst and a data analyst,

The first point we’ll check out is the actual goal of what these guys do see a business analyst is focused on finding trends to make sure that you know there are ways to check where the business aspect is going wrong in the present you know to use this kind of insight or use the trends that can that this person can see through the data and then have informed decisions.

Make informed decisions and of course, you know improve all the performance numbers you know you can have KPIs or key performance indicators which will indicate where what is lacking that can be assessed for that can be analyzed to find where you know things are going wrong and a business analyst can do that really well.

A data analyst is a person who has the capability to recognize information from raw data and then you know to make predictions based on the results that are at hand so a data analyst will be working with a huge amount of data sets when you directly compare it to a business analyst of course but then this again depends on the company depends on the projects and a lot of other things.

General the size of the data set the data analyst sees is definitely much bigger and then coming to the second point in comparison we have to talk about data source now where do business analysts get their data from seeing they will get most of their data from the initial project requirements and from clients themselves because when clients approach business analysts,

they’ll be like this is the problem we want to understand why things are working the way it is right now there are many types of business analysis out there predictive prescriptive descriptive many of these kinds and they’ll have a problem with one of those kinds of requirements where you’ll have to ask and you have to engage with the client a lot more and pick up all the data,

From them you know based on the project requirements and a lot more so that is where business analysts get their data from and then when we’re talking about data analysts we’ll be working with a lot of add-on data and when we talk about add-on data depending on the project or depending on the module.

You’re working on a project itself the data can change a lot of uh you know data can be split up from a massive data set into small data sets too and you cannot treat one entity of data in a similar way as another one right these guys get their data from the data engineering team and you know this mainly used for and then they mainly coordinate with of course the data scientists at hand and you know the data engineers to go on to produce stunning visualization and tell beautiful stories with the data.

The third point is problem-solving see a business analyst is a person who has the capability who has a requirement today’s world to be as descriptive as possible in terms of how one can go on to handle projects what is the goal definition and of course what requirement gathering needs to be done to take us from that particular point you know we call it a road bump.

Where do you go from this road bump and how do you cross this kind of a bump in the highway of business but then we talk about data analysts right these guys will uh perform a lot of types of analysis they’ll be using a lot of algorithms as well to make sure you know they can bring in the power of ml ai and all these things to go on to do predictive analysis.

Prescriptive analysis to gain a lot of insight about the data predictive analysis talks a lot about how your present situation can be mapped and how uh you know you can go on to predict what might happen in the future if the situation remains the same prescriptive analysis makes sure to find out what all wrong things that have gone through.

Now and then ask questions based upon that to make sure that they don’t occur uh you know again in time with this point number four we have to talk about I’m sure you guys are very curious to know the average salary of a business analyst and a data analyst now business analysts get an average salary of somewhere around ninety thousand dollars per year in the USA and around nine lakhs per annum in India.

Data analysts get a very competitive salary when you compare it to business analysts as well they get an average salary of 85 000 dollars per year in the USA and around eight lakhs per annum so the numbers are pretty similar and I would say a business analyst gets as much as a data analyst in today’s world because it depends on a lot of things it depends on a lot of skill how certified you are and what expertise you have in this domain.

The average salary numbers that you’ve seen and there’s a very good chance that you know you might have a friend or a colleague or you know someone you know who is earning a lot more than the number you see on your screen and that’s the beauty of anything analysis data analysis or be it business analysis and then now coming to the fifth point of this comparison we have to talk about the skill set.

Business analysts require certain knowledge in terms of how they can communicate well how well they can convey a story to stakeholders how good they are at negotiating you know for example price for performance and how good are they at handling data which will help drive the decisions and when it comes to thinking right business analysts need this kind of analytical thinking out of the box thinking per se to make sure that they can go on to gather or you know to gather and jump on a trend,

Work with a lot of data at the end of the use the data in an effective way see everyone can use data but then using it in an effective way requires some knowledge and business analysts are good at that and then coming to data analysis data analysts know how to work with data manipulation and of course, they’re going to require an in-depth knowledge of that on how well they can handle data,

All the concepts of data science data manipulation and data handling too and when I say data science I’m sure your interests are peak because data science is a notion of its own right well a lot of data science is actually required in the field of data analysis too in that particular case it definitely adds value.

If the data analyst in question knows and understands how data science or methodologies can be used to work with data and make his or her life a little easier in terms of work as well and then coming to the sixth point of the comparison we want to talk about user interaction for a bit because when we talk about user interaction right see who are business analysts talking to because most of the time they’re either talking directly to our customer’s clients they’re talking to the users they’re talking to system developers.

If they are looking at trends then they’ll be hunting for technology enthusiasts who can find ways on how they can rapidly you know go on to analyze what’s wrong with their business or how better uh can they go on to do business that’s the primary centric when we talk about business analysts now in the case of data analysts what usually will happen is that you know these guys will have extensive communication with a lot of SMEs as emis as in subject matter experts.

You require various technologies for example you require a person in a data engine who knows big data you’re going to require a data scientist who has the capability to drive a lot of algorithms and of course the data analyst himself is going to require a lot of knowledge about a lot of technologies.

Primary interactions that usually happen uh in the case of a business analyst and a data analyst and then I’m sure you guys are curious about the job roles that we have today for these designations see a business analyst can get involved in a lot of job roles be it in consulting be it product management b project management.

There is no lag or there is no dearth of roles for business analysts and of course for data analysts too because data analysts can be data scientists themselves it can be data architects data engineers they can be end-to-end specialists when it comes to working with data and of course driving some result out of it,

Taking a raw entity such as data and converting it to absolutely useful information which is worth its weight in gold is something a data analyst can do and when that is the requirement of today’s world, of course, there’ll be more than uh you know 10 15 designations that of course, you know to support the job role.

The eight-point on this comparison I’m sure you guys are curious about which is easier to learn right see business analysis is a place where your secondary skills will definitely be as important as your primary skills because here you’ll require a lot of knowledge and skill on how to strategize things and how confident you are.

Example convincing a client of a strategy or how confidently can you take your business across and use something entirely elsewhere to technology or be it a strategy and how best can it work or not you need confidence for that,

That is important or to understand the latest trends in the technology is very important for a business analyst and if you are inclined towards learning new things which might not have thousands of millions of users but you might have to know that it is a very powerful tool which will have you know amazing which will provide amazing insights in that particular case you should go on to pick business analysis.

In my opinion and that would be easier to go on if it aligns with your interests now coming to data analysis is something you should be looking at if you require technical knowledge because if you’re good at something technical if you know how to work with data let’s say you have a penchant you have a liking for data in that particular case and then definitely you should you know be looking at data analysis,

This will be very much easier to learn if you know how if you know your way around data and how to effectively uh use data more than what is easier to start up to see both of these domains have amazing documentation to start with so, in fact, you can get started with both of these in a structured way.

stay with me for a while I’m going to show you how if it comes down to what you should pick I definitely think you should look at where your interests lie what your career goals are what you’re interested in and then pick up one next point on the comparison between the business analyst and data analyst we have a primary focus.

What our business analysts focused on as we discussed uh you know they mostly are working on how they can create strategic business plans for the future assess key performance indicators or what we call as KPIs they’ll be building use case scenario be it positive use cases negative use case scenario to make sure that that doesn’t actually happen and these guys will have the capability to plan out an entire year if required on their business front to see where things might work where things might not work.

Where they might lose money where they can bring in a lot more money and with trends that thing keeps changing every now and then so they have to have the ability to scale themselves and their findings to make sure they align themselves with these latest trends too and the primary focus of data analysis.

These guys uh, first of all, yes they account for the data that’s at hand but they’re also responsible for a lot of other things too you know the primary focus is data primary focus is to analyze data and produce a good result a result which is not only uh you know informative but they have the capability to you know go on to talk with the non-technical audience and then convey this message or the result to them for example board members or superiors too not only these guys are also responsible for keeping the data safe consistent and reusable.

I told you data we’re generating a lot of data today and three things that you have to talk about is how safe is your data how well is your data stored and can we make use of your data effectively now those three questions I asked are in order of data safety data consistency and data reusability.

Data analysts need this kind of knowledge to work with that too and then coming to point number 10 team members who do business analysts and data analysts work with well business analyst works with CIOs CDOs analytics managers data warehouse engineers and a lot of other people who are going to give them the data that’s required to furnish and create a good business motive plan.

Data analysts with these guys you know these guys are working with technical experts 99 of the time but then of course if they have a business requirement business analysts can themselves work alongside data analysts or business managers too to help meet the requirements of the client in a way if the client came around with a lot of data.

If the data requires some amount of mining some amount of hunting through uh to you know get the eventual result that’s required so understand this it’s not a separate domain business analyst can work with data analysts hand in hand to in an organization and this actually happens a lot in today’s world and enough I am sure you guys have a question saying which is better or which should you pick see you can consider business analysis.

If your interests are more towards how you can go on to make an organization make better decisions a simple business decision such as saying how many items should I stock before Christmas if you stock only 10 but if you have a requirement for 5000 people want your product and if you have only 10 or let’s say you have a thousand you are going to lose business and now if you stock 10 000 but eventually at the end of Christmas if you sell only a thousand or something the rest will be you know staying stagnant in your inventory…

It might be taking space it might be taking money and of course, just the effect of producing much when it’s not being put to use now to avoid all these kinds of things and of course a lot of lot lot more if you are interested towards this business analysis is something you definitely should look forward to and then coming to data analysis,

Data analysis you know see you have to consider this if you are if you have a liking for data and if you are you know a person who likes puzzles let’s say in a very vague way because data itself is a puzzle and if you can hunt your way through this kind of a maze and if you can pick up detail from the data and then use that detail to drive certain decisions sometimes it is very important mission-critical decisions that you’ll have to drive out as well …

Dataflickr Team

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