What is Data Analytics?
Data analytics is the study of processing unprocessed data to come up with a conclusion. Many data analytics methods and procedures have been automated into mechanical procedures and algorithms that operate on raw data for human understanding. Raw data will be processed so that organizations can come up with calculated and insightful data.
The field of data analytics is huge. The four main categories of data analytics: Descriptive analytics: This describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?
Diagnostic analytics: This focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?
Predictive analytics: This moves to what is likely going to happen in the near term. What happened to sales the last time we had a hot summer? How many weather models predict a hot summer this year?
Prescriptive analytics: This suggests a course of action. If the likelihood of a hot summer is measured as an average of these five weather models is above 58%, we should add an evening shift to the brewery and rent an additional tank to increase output.
Why is Data Analytics Important?
Data analytics is essential for every organization as it converts raw data into valuable information.
The conversion of data will enable organizations to discover new opportunities. This will then pushes businesses into smarter moves, and more efficient operations which increases their profit while keeping customers happy. Decisions are made strategically based on numbers and data rather than emotions. Data analytics will help you understand what has happened, why a certain thing has happened, what might happen in the future based on the current trend, and as an organization, what can be done next. All these information will be generated through various software tools like spreadsheets, data visualization, and reporting tools, data mining programs, or open-source language for the best data manipulations.
Companies that use Data Analytics
Organizations, no matter big or small, use data to improve and grow. Here are a few interesting and well-known companies that use data analytics in their business process.
Tesla Data analytics is used in Tesla's self-driving car. Every Tesla self-driving car processes sonar, vision, and radar data using neural net software. These cars also use fleet learning where different Tesla cars share data with each other for better learning processes, improving their overall analytics processes. These data are shared to ensure our safety.
Spotify Are you familiar with Spotify's annual Spotify Wrapped Campaign? Spotify composes all the music that you have listened to throughout the year and gives you a summary of your listening habits to be shared on social media. This smart marketing campaign from Spotify is made to increase their brand awareness, which is made possible by data analytics.
Nintendo Are you a hardcore gamer? Data analytics makes games more responsive to your needs. While many other game brands use data analytics for the development and delivery of their games, one big example is Nintendo. The graphic chips in Nintendo analyze data and dynamically improves graphics and render so that high-quality visual with low to no lagging can be experienced by gamers. This is why a small device like Nintendo is powerful.
Data analytics is also used in games for computer character development driven by an algorithm that responds to player instructions. Data analytics is slowly bringing gaming to the next level where verbal cues will be enough for the game characters to act.
It has become clear that data analytics is and will be in demand in every industry. Let's look at some of the best Data Analyst Certifications for 2023.
A lot of data are being bombarded from different departments of an organization. Data that are not processed are wasted. If you have no idea on how to process data, then it will definitely be a difficult and long process. As a certified data analyst, you can jump past these hurdles. This data analyst course will teach you to collect data, model it and analyze it to help your organization to make the best decisions. Once you have gotten your certification, you will have a better understanding on how to manage data analytics environments, query and transform data, implement and manage data models, and explore and visualize data.
Data engineers are essential to a company's success in today's fast-paced business environment, where agility necessitates cross-organizational data collaboration. They spend their days unlocking data and putting it to use for groundbreaking insights and value because they know that cloud analytics is a crucial first step toward a more resilient business transformation.
This data analyst certification helps you understand the fundamental computing and storage technologies utilized to construct an analytical solution. Students will be taught how to interactively explore data in a data lake stored in files. Once you have completed this training, you can take the exam and be a certified Data Engineer on Microsoft Azure.
Do you have a good understanding of relational data, non relational data, big data and analytics? These understandings are important for mastering data in the cloud. The Azure Data Fundamentals certification instills the foundational knowledge required to build technical skills and begin working with data in the cloud. This certification will also allow you to explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Power BI is one of the learning objectives of this certification, where building blocks and how they work together will be discussed.
Data Scientists are needed in every IT industry thanks to the emergence of AI machine learning and data science. They will help their organization to visualize and deliver innovation, improve customer experience, increase revenue, and data scientist will enable their organizations to stay competitive. A certified Azure Data Scientist Associate will get to support a data-driven culture using rigorous scientific methods and algorithms to find solutions to business problems and explore opportunities that will enable the organization to reach its goals. Designing And Implementing A Data Science Solution On Azure course teaches to leverage the existing knowledge of Python and machine learning to manage data ingestion and preparation, and machine learning solutions in Microsoft Azure.
5. Microsoft Certified: Power BI Data Analyst Associate
This data analyst credential allows you to get insights without a mess. Power BI delivers insights from your data without the complexity. As a certified Microsoft Power Bi Data Analyst, you will be able to get advanced reports and discover new patterns in your data to make more confident business decisions for your organization. With Power BI, you can do more with your organization's data; from the boardroom to the call center, across the office, and around the world.
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All these Data Analyst certifications are both valuable and in demand. Data analysts are the catalyst for an organization to do better and compete in the current technologically advanced business environment. Investing in certification will definitely bring positive changes to employees, where expert people will be able to carry out the daily task effectively and efficiently. FAQ
How do I become a data analyst?
Get a foundational education.
Build your technical skills.
Work on projects with real data.
Develop a portfolio of your work.
Practice presenting your findings.
Get an entry-level data analyst job.
Consider certification or an advanced degree.
Are data analytics certifications worth my time?
If your organization focuses on processing and interpreting data, then yes! Gaining certification in data analytics will equip you with all of the necessary skills and know-how required to get the best out of available data and decisions can be made strategically based on numbers and facts.
What is the salary range for a data analyst in Malaysia?
The average annual salary for a data analyst in Malaysia is RM127,064. That is RM10,588.67 monthly.