Introduction to Data Analyst
The analyst, who inspects, cleans, transforms, and models data with the aim of concluding useful information from the given data, is called Data Analyst. They help in forming good conclusions and hence in proper decision making from the data. They help in the organization’s business by making better decisions. The essential skills of a data analyst include knowledge of SQL, programming language, and analytical skills. Many techniques involve in the analyzing process, and a data analyst should be well versed to do the analysis properly. Raw data has to be transformed into good information.
What is a Data Analyst?
There is a huge difference between a data analyst and a data scientist. People have confused data analyst and data scientist roles since they both sound similar.
It goes through the data and tries to identify the trends in the data. What do the numbers in the data tell? What decisions can be made based on this data? Are some of the questions which a data analyst asks while working on the data?
Data Scientists are experts at interpreting the data with expertise in coding and mathematical models. Most data scientists possess a PhD or master’s degree in data analysis. They have hands-on experience in machine learning, programming and can create a new process for data models using a predictive model along with data analyst work.
How does Data Analyst make working so easy?
It generally will retrieve the data, gather it, organize it, analyze it and use it to come to a certain conclusion. Their work varies as it depends on the type of data that they are working with (inventory, social media, sales, finance, etc.) or client project.
They can provide valuable data to the employers of the company who wants to know more about their customer and their needs. Companies in every industry can benefit from the insights that a data analyst provides.
They manage the database and helps the company to make decisions based on it. Let’s consider an example of a data analyst working with a marketing company that provides mobile ads. Here they need to build profiles of mobile application users and provide the ads relevant to the user over the platform. This will ensure higher returns when analyzing the advertising expenditure. It will also provide an enhanced user experience as by giving them a more personalized feel over the ads.
The following are the top companies:
1. Mu Sigma
Mu Sigma is one of the world’s largest data analytics companies. Their company’s name is derived from the statistical terms “(μ),” which stands for Mu and “(σ)” for sigma, which represents the mean and standard deviation of a probability distribution.
The company was founded by Dhiraj Rajaram in 2004, who is also the current CEO of the company. They provide services in marketing analytics, demand analytics, network planning, optimization, transportation analytics, risk analytics, and sourcing analytics etc.
It is a social business intelligence firm that provides Monitoring and analytics, Dashboard and reporting, Channel analytics and CRM and workflow services. They have many prestigious clients on their client list.
3. CBIG consulting
CBIG provides Business Intelligence (BI), Data Warehouse (DW) and Big data analytics services to clients. They also deliver data-centric initiatives which includes Predictive analytics, Marketing analytics, operational analytics, Cloud analytics, Data science etc. CBIG is one of the best data analytics company that will help you to get on the right track and start delivering results regardless of the state of your data.
GoodData markets big data analytics software and Business Intelligence (BI) for cloud computing. It was founded by Roman Stanek in 2007 with the name of “Good Data Corporation”. With GoodData, a company can empower their business by distributing the targeted analytics to all members of your business locations which includes customers and partners.
5. PricewaterhouseCoopers (PWC)
PricewaterhouseCoopers, also was known as PwC, are the largest professional services firm in the world. It was formed in 1998 by a merger between Price Waterhouse and Coopers and Lybrand. PwC, with the help of its platform, helps to optimize the data assets and make faster and better decisions. With its leading data and analytics services, pwc helps create a data framework, build the strategy, optimize the infrastructure and helps to create a culture to become a data-driven organization.
Deloitte is a multinational professional services network and also one of the “Big Four” accounting organizations. Deloitte turns information into useful and actionable insights by understanding the decision maker’s role to maximize analytics value.
Solutions which Deloitte provides are:
- Advanced analytics
- Enterprise data management
- ERP analytics
Deloitte analytics approach is filled with deep industry knowledge and functional experience mixed with technology.
KPMG is a professional service company and one of the big four auditors along with PwC, E&Y, and Deloitte. KPMG’s analytics, information, and modelling help organizations solve the mystery out of huge data and show them how to affect their data resources to produce better business output.
KPMG provides analytical services in the following fields:
- Consumer market
- Energy and natural resources
- Technology and telecommunications
- Financial services
What can you do with a Data Analyst?
A data analyst is more than just a number cruncher. An analyst reviews the given data and determines how the data can be used to solve real-life problems or help a company to grow its business. Analysts work with shareholders and different managers to know their vision and provide them with insights on how data will help them to achieve it.
Analysts help a company to plan ahead by evaluating the efficiency at which a company runs its operations on a daily basis with the help of data. They can also yield results related to forecasting the more or less demand from customers, and data measurements can be used for accounting and financial operations at the time of budgeting and project management to measure project duration and employee efficiency.
Working with a Data Analyst
Working with them is really fun as you get to learn different aspects of data and finding meaningful information. They help you to understand how to translate numbers into plain English that every business collects data related to sales figures, market research, logistics, or transportation costs.
They also require good communication skills to write and speak clearly and easily communicate complex ideas; this will help a person to improve his communication skills. Mathematics is one of the important parts of an analyst as a data analyst needs maths skills to estimate numerical data and plot the data on a graph or chart; working with an analyst will also help a person to improve his logical thinking and his mathematical skill.
- A data analyst helps to detect errors from a dataset, and with the help of data cleansing, improves the quality of data which ultimately benefits both institutions and customers such as the bank, finance company, etc.
- They work on a recommendation system that is mostly used by online retailers like Flipkart, Amazon, eBay, etc., where an analyst provides the most probable item that a user will like next by mining previous data.
- An analyst can also help a bank to identify probable fraudulent customers based on analysis made on historical data.
- Security agencies also make use of data analysts for surveillance and monitoring purposes based on a huge number of information collected and processed by an analyst.
- They give you the answer to the following questions:
- What is the current scenario?
- What has happened?
- Will it affect the business in a good way or a bad way?
- Why did it happen?
- How will it affect the company’s growth in the future?
- What is the possible outcome?
- How to prevent this?
To become a data analyst, one needs to have a natural understanding of math and statistics; the following are the basic requirement:
A person should have a thorough knowledge of statistics, starting from basics like mean, median, and mode to advanced topics like real analysis, graph theory, and numerical analysis.
Along with statistics, mathematics is also the most important subject in which a person should have depth knowledge. Topics like linear algebra are used with regression, understanding data structure and prepare data for predictive data modelling.
3. R and Python
For analytics purposes, Python and R are widely used tools as Python is easy to learn programming, which provides different statistics and mathematical libraries like numpy, scipy, sci-kit-learn, and matplotlib etc., whereas R provides advanced computing capability, graphical capabilities, and advanced tools.
4. Query Languages
A person wanting to work as a data analyst should be hands-on with the query languages like SQL, Hive, and PIG etc. SQL is a general-purpose language that is used for transactional queries. SQL is mostly used on a daily basis, but the only downside is that it does not support petabytes of data.
Hive is a Hadoop query language introduced by Facebook which can support terabytes and petabytes of data. PIG is used during the processing of both structured and unstructured data.
Having all the data is just not enough, as you also need to bring it to life. There are different data visualization tools which a data analyst can master, e.g. Tableau, Oracle Visual Analyser, SAS Visual Analytics, and Microsoft Power BI. Using these tools, a data analyst needs to make reports and communicate these findings to the top management.
Data Analytics job is named a “best job of the decade” by Glassdoor. There is a huge demand-supply gap for analytics professionals as there are more requirements and fewer data analyst.
Data professionals are primarily statisticians, engineers, data miners, and IT professionals. Companies are always in search of the best data analysts to boost their research and analysis departments. Data engineering plays a vital role in finance and Capitalization. They will get more research-based work compared to the other non-technical work.
Who is the right audience for learning Data Analyst?
Data analysis is an in-demand and lucrative career. A person who enjoys playing with data can become a data analyst with a good pay scale.
Anyone can become a data analyst and can pursue a career in it because it’s all about Matrices, calculus, integrals, and statistics. A person who is having even basic knowledge of these topics can become a perfect data analyst by doing some online certificate courses and gain practical knowledge along with theoretical knowledge.
How will this technology help you in career growth?
It uses a massive amount of data to work on current trends and make forecasts. The demand for a data analyst is very hot where well-known universities have started running courses and programs that are focused on data analysis.
A beginner who is working as a data analyst can master the domain with experience. He/she can in the future start their own analytical firm and help clients achieve their goals by providing useful insights and information. The growth of an individual as a data analyst is immense since everything is related to data in today’s world, whether it is social media or financial growth. Companies are willing to pay any amount of money to get the correct data which they can use it further for their growth.
This is the age of big data, where billions of data are being generated every day, and only a few hundreds of data are being processed. This is because of the shortage of data analysts in the market. They play a key role in a company by providing valuable data, which ultimately helps a company’s growth. This is the most demanded job in the century, and they are here to stay.
This has been a guide to What is Data Analyst. Here we discussed the working and advantages of Data Analyst with top companies that implement this technology. You can also go through our other suggested articles to learn more –