The 21st century has witnessed mounting advancements in the use of data and the establishment of data-driven businesses. In this world of big data and machine learning having basic knowledge of the field, its ability to analyze, interpret, and even question data is regarded as an extremely useful skill.
Business Analytics and Data Science are the two major areas of interest at the present time. Let’s discuss each one respectively.
What is Business Analytics?
Nowadays, every business houses a business analytics team within them, who are expertise in extracting estimations and conclusions from within the available data or the data that isn’t readily available, which needs to be scooped out, and presented in a relevant manner to the stakeholders, for them to make an informed decision. For every business to thrive and stay competitive in its domain, there is a need for steady improvements and increased efficiency in business processes to cut corners and streamline the business.
Business Analytics is an approach to understanding the gathered data, estimating business performance, and assembling valuable conclusions that can assist companies to produce informed decisions on future businesses.
What are the tools used for Business Analytics?
Business Analytics is performed through various tools such as Qlik, Splunk, Sisense, KNIME, Dundas BI, TIBCO Spotfire, Tableau Big Data Analytics
Are there any divisions to Business Analytics?
- Descriptive Analytics
Considered the simplest form of analytics, as it describes the data in order to understand what has occurred in the past or what is currently happening. It employs data aggregation and mining techniques. Descriptive analytics makes data more convenient to members of an organization such as investors, shareholders, marketing executives, and sales managers.
2. Diagnostic Analytics
Diagnostic Analytics makes use of probabilities to evaluate why a particular thing may happen. It is mainly used to identify the root cause of something.
3. Predictive Analytics
Predictive Analytics is the type where the analyst foretells the possibility of a future event with the aid of ML techniques and a statistical model
4. Prescriptive Analytics
Prescriptive Analytics as the name suggests put forth recommendations for the next best action to be taken. This method identifies the relation between actions and their outcomes.
Who is a Business Analyst?
A Business Analyst is a person who undertakes to examine the business’s procedures, the products and services that they offer, and the systems to upgrade current processes and produce profitable decisions through insights and data analysis. A Business analyst backs up the organizations to document business processes by evaluating the business model and blending it with technology.
What does a business analyst do?
- Business Analysts try to identify what businesses do
- Decide on how to better existing business processes
- Find out the steps or tasks to support the implementation of new features
- Formulate the new features to be implemented
- Examines the impact of implementing new features and put the new features into practice
Which skills required?
Analytical Skills– is the ability to identify and solve complex problems concerning the business. Examples of Analytical skills include; critical thinking, data analysis, communication, and research.
Leadership Skills– A Business Analyst should be a good leader with the ability to direct team members and predict the budget.
Business process and planning– Planning the project scope, understanding and implementing requirements of the project, identifying resources required for the project are important for a business analyst.
Technical Skills– Obviously when in an IT sector you are expected to know a few technical aspects like operating systems, hardware capabilities, database concepts, networking, SDLC methodology, etc.
Business analytics is making headway in the domain of Data Science. Also, as a term often used synonymously with Data Science, business analytics has to scope in every field that wants to advance the way they measure data to make insights. Business analytics is applicable to all companies that use data-driven decision-making.
What is Data Science?
Data Science has advanced to be the most reassuring and in-demand path for skilled professionals. Industries require data to make them make careful decisions. Data Science converts raw data into meaningful insights. Therefore, industries need data science. With the onset of computing processes, cloud storage and analytical tools resulted in the field of computer science integrating with statistics thereby leading to the emergence of Data Science.
The simplest definition of data science is obtaining actionable insights from raw data. Data Science is the process of collecting, analyzing, and interpreting an extremely large amount of data.
Who is a data scientist?
In simple terms, a Data Scientist is a person who is an expert in the collection, interpretation, and analysis of huge amounts of data, having the technical skills to solve complex problems, moreover the curiosity to explore what problems need to be solved.
A data scientist is like a sculptor who carves and shapes the data to create something meaningful out of it. A data scientist must have an intrinsic eagerness and curiosity that drives their need to find answers. Data scientists give meaning to data.
Data science tools:
SAS, Apache Hadoop, Tableau, Tensor Flow, BigML, RapidMiner, Excel, Python, SQL, Java.
- Increases business predictability
- Ensures real-time intelligence
- Favors the marketing and sales area
- Improves data security
- Help interpret complex data
- Facilitates the decision-making process
Python, Lean statistics, Data Collection, Data Cleaning, Analytical curiosity, storytelling, interpersonal skills like communication, presentation, multifunctional collaborations, intrinsic eagerness
Data Science jobs are one of the most sought after and liked jobs around the world. Data Scientists are popular in IT and healthcare and have a strong presence across a multitude of industries. Almost all industries nowadays rely on data science to make smart and sharp decisions that are based on the data that demote consumer preferences and aids to market it to the right group of people.
Indeed business analytics as the name implies is the study of a business’s functioning to make insights out of it and make predictions. Data Science makes use of statistical methods, techniques, and algorithms to formulate meaningful insights out of large data sets. Data-driven companies view data as an asset and continuously try to manipulate it for competitive advantage. Business Analytics and Data Science thus are two similar yet totally different disciplines that are transforming the market at a faster pace.
To mark the grade in Business Analytics or Data Science you definitely need to be well acquainted with the areas. Attending training in Business Analytics and Data Science would benefit you tremendously. A certificate could lift up your career!