Career opportunities you can explore in the field of data science itself and those are
=> Data analyst
=> Data architect
=> BI analyst
=> Data engineering
How is a data analyst
Data analyst are the real troopers of the data science these are the one who is involved in gathering data structuring database, creating and running model and preparing advanced types of analysis to explain the patterns in the data that have already emerged. He also overlooks the basic part of predictive analytics. That is the “elevator pitch of the data analyst”. But to get an idea of what it means to be part of a team like that, we need to look at what data analyst does. A data analyst both a thinker and a doer who does not hesitate to roll up their sleeves and Dig into the numbers. Data analyst extract and analyse the data with a can-do approach and then present data-driven. They also develop and build analytics models and approaches as the basis for a company's strategy and vision. And also responsible for the identity and extracting key business perform, Risk and counting it into easy to digit format. So, as you can see it the agility to shift between strategic predictions and operational activities is a must. These are great team players and work closely with various departments and leaders within the organisation. That is super important if they want to effective in their roles. So, the ability to communicate well and influence is a critical lure. So, what does it all mean is a team of salary how much a data analyst will earn? If you take the first four steps in the career you can expect an average of $68,000.
How to become a data analyst
Are you now considering a career as a data analyst? As we mention the certainly a great option to explore both on its own and as a gateway into data science. There are several points you should consider before you can determine with confidence whether is a career in data analytics is the best career path for you. Skills that are needed for data science is technical, practical and soft.
You have to need some knowledge of programming in python, R, SQL. In that sense, it would be optimal if you know how to extract and analyse data from diverse resource knowledge of tableau and how to work with large data sets is also a very big plus. A good grasp of statistics and the ability to work with some of the best statistical software packages. But know your way around quantitative methods confidence etc
• Who is the Data Engineer?
• Salaries?
• Skills?
• Academic background?
Data Engineer is the Jedi knights of data science. They rely on a blend of analysis, wisdom, experience and judgement to make key decisions for a company's success. a data engineer is a self-starter who is inspired to complete more than your usual number of tasks. Data engineer are the ones to take further up the data science pipeline. they use the data architects to work as a stepping stone and then pre-processes the available data. these are the people who ensure the data is clean and organised and ready for the analyst to take over. Data engineer also implement complex large-scale big data projects with a focus on collecting managing analysing and visualising large data sets. All that massive amount of overwhelming raw data? Well, they are the ones turning it into insights using various toolset, techniques and cloud-based platforms you might think that’s enough work for one day? Not for a data engineer. Data engineers are also responsible for building and maintaining ETL pipelines which makes crucial data accessible for the entire company. And when they get a minute, they lend a helping hand to BI analyst by designing and supporting BI platforms. Who makes sure all big data applications are available and performing properly? Again, data engineers. And to top it all of their great team players. A data engineer knows how to actively collaborate with data scientist and executive to build solutions and platform that meet or even exceed a company’s business need. So how do all these responsibilities translate into the data engineer salary?
Salaries?
Glassdoor, pay scale
US
<1 year of experience -> $103,000
4-6 years of experience -> $117,000 (plus $10,000 bonus)
UK
<1 year of experience -> £30,000
1-4 years of experience -> £41,000
5-9 years of experience -> £54,000
Academic background?
A degree in software engineering, computer science or information technology will give you a flying start. However, if that’s not the case you can still make it out. But you still need skills in computer programming and software design statistical modelling and regression analysis, python, SQL and machine learning Now before rush into the writing of your dream job you should know that acquiring these skills is possible even for complete beginners today, there are plenty of qualification programs and online certificate data science training. Once you complete the courses and gain experience with real-world exercises and projects you will have the skills, confidence and the portfolio to apply for a data engineering position.
Next, let's talk about skills and qualification what do you need into this department to become a data engineer? Well as we mention a data engineer jobs comes with certain responsibilities so, here is a list of competencies and skills you need to become a data engineer who knows their stuff
Skills
For a data engineer knowledge of data modelling for both data warehousing and big data is a must along with experience in big data space (Hadoop stack like HDFS, Pig, Hive etc). Of course, the ability to write, analyse and debug SQL queries will help you score high on an employer’s recruitment list. One more hint show you gain some experience with at least one scripting language for example python and don't forget the basics mathematics is never out of style in the data science competitive universe
Practical skills
Data visualisation skills, analytical skills, decision making, personal responsibility, clear processes for monitoring work and measuring results, design of feedback loop into work, strong attention to detail, critical and conceptual thinking
BI analyst
If you are looking into considering a career as a BI analyst great choice. BI analysts are some of the most in-demand Data science professionals across many industries and business fields at the moment. however, if you lack academic background are relevant skills for the job it’s easy to get discouraged. That said you should know that acquiring these skills is possible even for complete beginners.
There is plenty of qualification program and online certification data training building up your programming skills happens naturally with the course on python, SQL, and R and plenty of exercises and projects to you make your knowledge stick. Once you are comfortable with programming the program teaches you how to create a machine and deep learning model with the latest frameworks like TensorFlow and TensorFlow 2. And if you are like to build a major specialised skill set you can do with that.
Of course, on-time series analysis credit risk modelling and more as we mention there are plenty of a real word exercises and project and data science as a field evolve so do the training with new course and resources getting added. Alright let's talk about the BI analyst and everything you need to know about that Career choice first thing first becoming a BI analyst is one of several ways to get yourself on the data science track and if that what your aiming for just keep in mind the other options so who is the analyst and what makes them so special. BI analyst is fierce business performance and ninjas possess a blend of business vision they join forces with senior management to shape and developed a data strategy analysis of key performance indicators accurate overview of businesses performance and identifying areas that need improvement are also a speciality in BI analyst Domain. So far so good but what exactly does a BI analyst do. well, they focus primary and analysis and reporting of past historical data. Once the relevant data is in hands of BI analyst, they must quantify the observation calculate KPI’s and examine of course the most important aspect of a BI analyst job is to continuously improve. Therefore, they examine their competitors' data trends, seasonality and other random effects to quickly identify issues and but practice on top of that they create killer graphs and dashboard to review the major decision and so In a word if you want to have an important on the business world become a BI analyst. well, maybe that’s easier said than done. well according to Glassdoor and pay scale if you are new to the profession you can count on $66000 average pay. Once you are gained a few years of experience and you can and have the persuasion skills you can reach up to $79,000.
So what are the steps and qualifications you need to become a BI analyst in the first well if you want to pursue the BI analyst career path consider gaining some experience a BI analyst career has a lot of offer but you need some high-level skills to get started in generally landing a job as a BI analyst should come relatively easy if you have a B.A in one of your following computer science finance business administration but don’t be quick to discourage if your background is contemporary dance or classical Indian literature because as we mentioned, in the beginning, there are plenty of specialisation and all around online certification course that will give you the knowledge and confidence here a small tip if you are new to data field an internship in the finance industry would be great start not only will this help you understand all the business processes but you also get ok.
From academic to competitive data science job market here are the skills you need a data science job is all about the skill set and the BI analyst part market no exception there is a plethora of technical practical and set of skills you should work can to fit? Just take a look at the technical side of the things we have excellent Excel, SQL, Power BI scales along with some serious tableau desktop and server abilities and those are major importance to a BI analyst job how about python and R. highly desirable so make sure you can put them on your things to learn list to all in all if there is a tool or technique that will help you identify analysis and interpret trends are patterns in the complex data sets just master it. OK what about practical skills song planning skills and organisation skills impeccable attention to details working independently in a fast-paced and rapidly changing environment and designing rich data visualisation
Data architect
If you are seen in the 1999 cult movie the Matrix you probably recognise the architect as the greater of the utopian world for the human mind to inhabit. much like their blockbuster counterpart data architect create the database from scratch. They design the way data will be retrieved, proceed and consumed that was the teaser trailer of the data architect job. the architects are technical experts who adapt data flow management and storage strategy to a wide range of businesses and solutions besides data architecture control access to data so all you corporate spies out there now you know who look for. Data architects are also responsible for design patterns data modelling service-oriented integrated and business intelligence domains strategy goals. A data architect constantly seeks out innovation to provide improved data quality and reporting to eliminate redundancies and provides better data collection sources methods and tools.
So how much do data architect make? We consulted with a glass door and PayScale to give you the numbers. according to Glassdoor salaries report the average annual paper entry-level data architect in the US is approximately $104,000 while professionals with 4 to 6 years of experience make more than 125000 dollars and you can easily get a bonus in the region of $10,000 per year. that said it's time to answer the blog the big question which is how to become a data architect? If you are now looking forward to starting a career as a data architect great choice the data architect role is on the rise. With its increasing importance for an entrepreneur and their business success that the data architect career path is the right one for you. let’s start with the academic background field will give you a competitive edge but don’t be quick discourage for if you are studied something entirely different it turns out these are by no means prerequisites to get the job. experience than in shiny degrees in their own word’s bachelor degree in computer sciences desirable but will waive this the requirements entirely if you have significant and applicable first of all. master Python, ‘R’, SQL, tableau and gain experience in data Modelling and machine. the good news is that even if you are like the qualification there are ways you can build up your knowledge from scratch be it by taking some additional qualification courses or by enrolling is an online certification data science training. speaking of qualification what are the Data Architecture must-have skills you should acquire? that means you will need a robust skillset including technical practical soft skill to see the ultimate list you got to you how some strong data modelling skills experience in Python, ‘R’, SQL, of course, you should not be limited for this thing. that said you can only benefit from some knowledge in XML, Java then comes to 3D. you should strive to add to your database architecture and finally being familiar with data retention concept and Practice is a plus along with understanding automation of data flows and integrations. the practical skills so a data architect can lead multiple highly Complex efforts simultaneously establish and implement standards and guidelines determined key architecture solutions that meet performance reliability and evaluate emerging data management Technologies for applicability and adoption present technical concepts to upper-level management and officer, work independently employee strong problem solution skills execute task with impeccable to details. yes the soft skills although there is nothing out of ordinary here, soft skills are sometimes the hardest leadership and guidance to your project team necessary
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