Data Analysis can be tricky for some students. Make your life easy with an expert!
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#1 in Data Analysis Tutoring & Homework Help
If you are doing a course in Data analysis and need expert help, we can help.
MEB has an elite pool of Data science tutors who are experts in Data Analysis. If you are looking for help, you are at the right place! Whether you searched for ‘Data Analysis tutors near me’ or ‘online Data Analysis tutors,’ we can help.
How can MEB help you with Data Analysis?
We provide the following services related to Data Analysis :
Data Analysis tutoring online (1-on-1 private sessions)
Whom do we help with Data Analysis (Data Analysis )?
We help college and university students primarily studying data analysis in the USA, Canada, and Gulf countries. Since we provide online services, we help students globally. We also help businesses in analyzing their data.
Do we do your Data Analysis assignment?
Yes, we do. If you are a student struggling with Data Analysis homework/assignment, we can help. Managing the academic load is critical. So, hiring someone to do your homework due to intense academic pressure is fine. WhatsApp now to get help. We are waiting to help you.
How do I get started?
Getting started with Data Analysis through online tutoring & homework help is easy. Whatsapp us your requirements, and one of our Data Analysis expert tutors will check it and let you know the fee. In the case of tutoring, we have standard fees that you can check on our pricing page. You can make the payment that we agreed on, and you will get the service requested. The process is the same whether you want online teaching/tutoring or help with your assignment. WhatsApp us to get started.
Why chose MEB?
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How much does online Data Analysis tutoring cost?
Data Analysis tutoring costs anywhere from $25/hr to $40/hr. The cost depends on the experience and quality of the tutor, the number of sessions you want, and the depth of explanations you require.
How much does Data Analysis homework help cost?
There is no standard fee, and it varies from homework to homework. Factors like the deadline, effort, tutor’s quality, etc., determine the cost. Check our pricing page for more info.
About Data Analysis
What is Data analysis?
Data analysis is the process of setting objectives, collecting data, cleaning data, analyzing data, and finally presenting the results. It helps in making better and informed decisions.
Data analysis 5-step process in detail
To gain meaningful insights from the data, we follow the 5 steps below.
1. Setting objective
Setting a goal is the first step in data analysis. To set the goal, we must understand the business/organization first and what is the most crucial aspect that we want to improve. For a business, it could be increasing sales, improving customer retention, bettering customer satisfaction, etc. For a government organization, it could be improving the healthcare of the people, winning the election, knowing the mood of the people before implementing any new policy, etc. As different businesses work differently and can have varied objectives, a thorough analysis of the business history, business metrics, and KPIs (Key Performance Indicators) is a must. A data analyst must get a feel of the industry and business before starting the actual data analysis. It may involve talking to the senior management, employees, and customers directly or viewing previously recorded videos or interviews.
2. Collecting data
Once we set the business objective, we should start collecting data. We need to identify the sources where we can get valuable data. In the case of established businesses, there is usually a lot of data already. It can be about the customer’s transaction history, their behavior on the company’s website before they decided to buy or not buy, what prompted the customer to make the payment or what deterred the customer from paying, and what they usually do after making the purchase, etc.
There can also be data from the feedback form (online or offline), customer helpline chats and calls, and so on. Most companies use tools like SAS, Pimcore, Xplenty, Salesforce, etc., which makes collecting data a lot easier. Data that comes from the same business that we are analyzing is called ‘first-party data, and it is the best form of data one can get.
Data that we get from the competitors are called second-party data, and that from other sources is called third-party data.
The data that we get can be either qualitative or quantitative.
Dealing with such massive data requires data management platforms or DMP. Some examples of free DMPs are Dash Builder, Graphana, and freeboard. Paid applications like Databox and Dasheroo are also widely used as DMP, along with Python libraries like Pandas and several other R packages.
3. Cleaning data
There can be significant errors, duplicates, and outliers in the data that require cleaning. We also need to remove unwanted data and structure the data, and if there are major gaps in the data, we need to fill them. Having the best data for data analysis is vital for its success; hence we should demote our maximum time on it. A good data analyst devotes almost 70-90% of their time to clean the data. We can use tools like Data Ladder and Python libraries like Pandas for data cleaning.
4. Analyzing the data
Univariate & Bivariate analysis, Regression analysis, and Time series analysis are the primary methods for data analysis.
Descriptive, Diagnostic, Predictive, and Prescriptive are the types of data analysis.
5. Sharing the results
The final step in data analysis is sharing the result, and it should be an honest presentation of the facts and figures with easily digestible and implementable recommendations.
Data visualization tools are critical in effectively presenting the results. Some prominent tools are Google charts, Tableau, Infogram, and Data wrapper. Python libraries like Plotly, Seaborn, and Matplotlib are also quite powerful and effective.
Organized presentation of the data analysis findings and suggestions are vital to passing the information to the organization’s top management, who might not know anything about the whole process.
Any industry that collects tons of data needs a Data analyst to find hidden trends and improve existing business flows to take its business to the next level. Private equity firms, investment funds, banks, and hedge funds in the financial sector need data analyses. Healthcare, E-commerce companies, insurance, marketing, retail, and technology firms need data analysis to improve their business. Big data generating companies like Facebook, Amazon, Netflix, Google, etc., go insane levels while analyzing their data.
Do I need a tutor in Data Analysis?
Yes, you may need a tutor in Data Analysis as it is one of the most challenging fields of Data science. It is a relatively new field with ongoing research, so learning it on your own is hard. A tutor can make the concepts much easier to understand. If you need an expert tutor in Data Analysis, feel free to WhatsApp us, and we will connect you with an excellent tutor.