Marketing Analytics and Reporting

Become a DATA ANALYST with NO experience[Video 31]Google Data Analytics Certificate – Course 1

Become a DATA ANALYST with NO experience[Video 31]Google Data Analytics Certificate – Course 1

The FASTEST WAY to Become a DATA ANALYST with NO experience as presented in this video, is to enrol in the Google Data Analytics Certificate program offered by Coursera, if you have not done so already.
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The Google Data Analytics Professional Certificate by Coursera is advertised as a Go-To Certificate to get you, your dream job as a data analyst with NO experience or college degree!

Enrol for free here

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Do you know that there are lots of great reasons to earn this certificate, now? Maybe you’re thinking about starting a career in the exciting world of data analytics, or maybe you’re just fascinated by the power of data as I am. No matter what brought you here, you’re in the right place to kick-start a career and learn industry-relevant skills in data science & analytics.

But first, what exactly is data? Well, I’ll like to say that data is a collection of facts. This collection can include numbers, pictures, videos, words, measurements, observations. Once you have data, analytics puts it to work through analysis.

Core duties of a Data Analyst as promoted by the Google Data Analytics Certificate program:

The analysts organized tasks and activities around the six phases of the data analysis process:
1. Ask
2. Prepare
3. Process
4. Analyze
5. Share
6. Act
The data analyst asked questions to define both the issue to be solved and what would equal a successful result.
Next, the business analyst or data analyst prepared by building a timeline and collecting data with for example, employee surveys that were designed to be inclusive.
The data scientist or analyst processed the data by cleaning it to make sure it was complete, correct, relevant, and free of errors and outliers.
The data analysts analyzed the clean employee survey data.
Then the analysts or people analysts as they are sometime called shared their findings by means of clean data visualization and recommendations with team leaders or top management.
Afterward, top management acted on the results and focused on improving key areas of the data analysis

Key data analytics terms explained in brief:

Analytical skills: Qualities and characteristics associated with using facts to solve problems
Analytical thinking: The process of identifying and defining a problem, then solving it by using data in an organized, step-by-step manner
Attribute: A characteristic or quality of data used to label a column in a table
Business task: The question or problem data analysis resolves for a business
Context: The condition in which something exists or happens
Data analysis: The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making
Data analyst: Someone who collects, transforms, and organizes data in order to draw conclusions, make predictions, and drive informed decision-making
Data analytics: The science of data
Data design: How information is organized
Data-driven decision-making: Using facts to guide business strategy
Data ecosystem: The various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data
Data science: A field of study that uses raw data to create new ways of modeling and understanding the unknown
Data strategy: The management of the people, processes, and tools used in data analysis
Data visualization: The graphical representation of data
Database: A collection of data stored in a computer system
Dataset: A collection of data that can be manipulated or analyzed as one unit
Fairness: A quality of data analysis that does not create or reinforce bias
Formula: A set of instructions used to perform a calculation using the data in a spreadsheet
Function: A preset command that automatically performs a specified process or task using the data in a spreadsheet
Gap analysis: A method for examining and evaluating the current state of a process in order to identify opportunities for improvement in the future
Observation: The attributes that describe a piece of data contained in a row of a table
Query: A request for data or information from a database
Query language: A computer programming language used to communicate with a database
Root cause: The reason why a problem occurs
Stakeholders: People who invest time and resources into a project and are interested in its outcome
Technical mindset: The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way

This certificate program is a great first step in your journey to finding a job you love.

NOTE: Databit365 does not in anyway claim ownership of this video.

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