It is predicted that the innovative market related to Data & Analytics will surpass a value of 684 billion dollars by 2030, aligning with this year where Forbes ranks jobs related to Data as one of the top 10 most in-demand jobs. Therefore, no one can deny the importance of Data & Analytics, as it is a science embedded in various Big Tech industries and is a key mechanism for companies undergoing Digital Transformation. Today, G-Able will delve into why modern companies cannot do without Data & Analytics!
What is Data & Analytics?
“We all learn from the past to make the future easier.” This fundamental definition of Data & Analytics sounds simple and straightforward. However, in this era where data flows in and out of organizations through various channels, using data to its maximum potential is not an easy task. Hence, there are professions that have emerged to manage, analyze, and leverage data to drive companies in various directions strategically.
Steps in the Data & Analytics Process
The steps or workflow of Data & Analytics are not set in stone. Some roles may only be responsible for specific tasks, but to broadly outline the responsibilities of the Data field, the steps are as follows:
- Asking Questions: It starts with posing questions – what information is needed, and what is the purpose of the desired data?
- Data Collection: In today’s era, where data is constantly pouring in, having a system that supports systematic data collection is crucial. Therefore, companies should begin by creating an efficient infrastructure for collecting data both externally and internally.
- Data Cleaning: Not all incoming data is complete. Some may be missing, duplicated, or erroneous. Cleaning the data is a crucial step to prevent inaccuracies in the analysis.
- Data Analysis: Analyzing the collected and cleaned data using various tools such as Microsoft Excel, Python, Apache Spark, R, Microsoft Power BI, and many others.
- Data Interpretation: Sometimes, data can lead to trend predictions or future insights that can guide business decisions. This step is exciting for data scientists as it involves interpreting data to anticipate trends or future directions for the company.
- Data Presentation: Often, analyzed or interpreted data can be complex. Presenting it in an easily understandable format, such as using infographics, helps make the data accessible to everyone.
Why is Data & Analytics Crucial for Organizations?
In any industry, data is considered crucial, especially in rapidly changing environments that require early market access.
Know Your Customer
Understand who the customers really are and determine the best channels to reach them. Building a streamlined data system, the single source of truth, helps in understanding markets and customer bases accurately.
Insight
Good insights are more valuable than half the battle won. Data & Analytics provides unbiased insights derived from accurate databases, enabling companies to formulate effective marketing plans and address real pain points.
Minimize Risk
No one can predict the future with 100% accuracy. However, with comprehensive data, risks, returns, and investments can be assessed to find the most optimal plan.
Importance of Various Sciences in Data & Analytics
With the rapid development of cutting-edge technologies in recent years, various scientific fields have become essential for Data & Analytics, making it like integrating new innovations to enhance efficiency, accuracy, and speed in analyzing vast amounts of data.
Artificial Intelligence (AI)
AI or Machine Learning shares similarities with Data & Analytics, starting from data collection, cleaning, processing, to presenting results swiftly. The synergy between AI and Data & Analytics has become more evident, with AI aiding in faster analysis, real-time insights, and what is known as Augmented Analytics.
Cloud Infrastructure & Data Center
With data constantly flowing in and out of organizations, efficient data storage that can connect with every unit is key to creating an efficient and effective Data & Analytics system. Having comprehensive and well-rounded data results in better analysis and decision-making.
DataOps
Integrating Data & Analytics as an extension of existing office software or applications can streamline tasks for those working with data. It is a new approach that makes working with data easier without requiring extensive programming knowledge.
In conclusion, the principles of Data & Analytics are something every modern business should have. It is the underlying plan behind the success of crucial Executive Decisions. The availability of tools, from AI to Cloud, makes Data & Analytics easy and fast for your decision-making process.