Businesses today are moving in a fast-paced environment. Innovations are offering more effective solutions to organizations than ever before. Analytics is a vital factor that has led to more business success in recent times. The field has grown from simply displaying facts and figures into more collaborative business intelligence that predicts outcomes and helps in decision-making for the future.
The basics of business analytics
Business analytics is a set of technologies and disciplines for solving problems using statistical models, data analysis and other quantitative methods. It incorporates an iterative pragmatic exploration of an organization’s data, emphasizing statistical analysis to drive decision-making.
Data-driven companies treat their data as an asset and actively try to find ways to turn it into a competitive advantage. The success of data analytics lies in the quality of data and the use of skilled analysts who understand the business and technologies. These analysts should also commit to managing data to gain insights that inform the decisions of a business.
How do business analytics work?
Before data analysis can occur in any business, there must be a business analytics system in place. It starts with several foundational processes:
- Determining the business’s goals
- Selecting an analytics methodology
- Acquiring business data to carry out the analysis
- Cleaning and integrating data into a single repository, such as a data warehouse.
The initial analysis is conducted on smaller sample sets of data. The tools used in analytics range from spreadsheets with statistical functions to predictive modeling and complex data mining applications. They reveal relationships and patterns in raw data. New questions are posed, and the process continues until the goals of the business are met.
The deployment of predictive models involves scoring, which is a statistical process, and typically uses records in the database. Scores aid organizations in making more informed real-time decisions within business processes and applications.
Business analytics also supports technical decision-making in response to unpredictable events. The process can be automated using artificial intelligence to support real-time responses.
Types of business analytics
There are four main types of business analytics. These include descriptive, predictive, diagnostic and prescriptive. There is also an emerging type of analytics called cognitive analysis that uses machine learning, deep learning and artificial intelligence.
Descriptive analytics
This type of analytics looks into historical data to determine a unit’s response across a set of given variables. It tracks key performance indicators, also called KPIs, for a better understanding of the state of a business.
Descriptive analysis involves these steps:
- Determining the business metrics that will evaluate performance against objectives.
- Identifying the data needed according to the state of the business.
- Collecting and preparing data using methods such as transformation, cleansing and depublication.
- Presenting data in graphs and charts to make it easily understood by non-analytics experts.
Diagnostic analytics
This is one of the types of analytics that assists individuals in understanding why certain things happened in the past. Analytics professionals use data mining, drill-downs, correlations and discovery to understand the driving factors.
Diagnostic analytics is an advanced form of analytics. It is typically employed before descriptive analysis to determine the logic behind results in marketing, finance, cybersecurity and other aspects. Some examples of diagnostic analytics include identifying technical issues, examining market demand, improving organizational culture and explaining customer behavior.
Predictive analytics
Predictive analytics looks at trends in historical data to determine the probability of certain future outcomes. It uses several techniques, such as machine learning algorithms, data mining, and statistical modeling, to forecast the likelihood of events.
These analytics assist in enhancing business areas such as efficiency, customer service, risk management, and fraud detection and prevention. It can help maximize profitability, improve business operations, establish customer responses and cross-sell opportunities. Examples of predictive analytics include detecting employee intentions, predicting customer preferences, predicting staff and resources, and recommending products.
Prescriptive analytics
Prescriptive analytics creates recommendations to handle similar future situations by looking at previous performances. It uses various tools, machine learning algorithms and statistics for internal and external data. Analytics professionals can obtain insights into what may occur, when and why. Some examples of prescriptive analysis include:
- Enhancing equipment management
- Tracking fluctuating manufacturing prices
- Price modeling
- Coming up with the best course of action
- Identifying testing
- Evaluating rates and readmissions
Cognitive analytics
Cognitive analytics is the newest entry in business analytics. It combines artificial intelligence and data analytics to look at the available data in the knowledge base and develop the best solution to the questions being posed.
These analytics cover multiple analytical techniques to scrutinize large data sets and monitor emerging patterns and customer behavior trends. This might entail tapping into unstructured data sources such as texts, images, social posts and documents.
How to become a business analytics professional
Becoming a business analytics professional requires acquiring skills and credentials applicable to the industry and work that interest you. Here is a roadmap to becoming a professional in this field.
Sharpening business analytics skills
The first step toward becoming a specialist in business analytics is developing the right analytics skills. These skills will assist you in analyzing data and coming up with the right solution for the business.
Taking a course
It is essential to familiarize yourself with the knowledge expected from an analyst. These professionals need to stay up to date and ensure what they know is sufficient to qualify for different positions. Online or in-person coursework can give an individual the right tools to get their foot into the data analytics door.
Many business analytics and data analytics courses can offer individuals a holistic understanding of the job. Analytics professionals should also familiarize themselves with the tools used in business through coursework in Excel, Tableau and MySQL.
Obtaining a business analyst certification
Another great way of expanding your skills and potentially enhancing your earnings is acquiring a certification. These certifications will show potential employers that you have received a certain amount of training and how much you know about business analytics. One needs to start with basic courses and move up to more advanced ones for the best learning experience.
Earning a degree
Many employers prefer individuals who have degrees. While some may be happy to accept a bachelor’s degree, others prefer candidates with a master’s degree. You can earn an online business analytics master’s at an accredited institution like St. Bonaventure University to advance your knowledge and skills and gain a competitive edge in your job search.
Start with an entry-level role
Aspiring data analytics professionals can seek internships and entry-level positions in finance, accounting or business settings. These will help in building experience before advancing to a higher position. They can also look for titles such as “junior business analyst” or “entry-level business analyst” in a job search.
Skills required to work in business analytics and how you can improve them
Here is a look at some of the skills business analytics experts should possess to succeed in this highly critical and often complex work.
Technical skills
The following technical skills are required to become a good business analytics professional:
Statistics, probability, and mathematics
Probability and statistics are the foundation of business analytics. They help individuals understand numbers to conduct hypothesis testing, regression analysis and probability theory. Analysts must also be proficient in mathematical concepts such as calculus, algebra and linear programming.
The following steps can help improve your statistical and mathematical skills:
- Take online courses or attend seminars offering mathematics and statistical analysis training. Many online platforms and universities offer courses that teach individuals statistical analysis and mathematics.
- Work on challenging mathematics and statistics problems.
- Practice with statistical software to conduct statistical analysis on data sets to enhance your statistical analysis skills.
Data mining and analysis
Data mining in business analytics turns raw data into useful information by identifying hidden trends and patterns. Professionals must collect, process and analyze large amounts of data from different sources. They should also be able to find patterns, outliers and trends in the data and use the information to provide recommendations and insights.
To improve on data mining and analysis skills:
- Learn how to work with different data types, such as structured and unstructured. The former is organized, while the latter is not organized. Individuals can enhance their data mining and analysis skills by understanding how to work with both sets.
- Be proficient in data visualization tools such as Excel, Tableau, or Power BI. These tools assist individuals in creating visual representations of data, making it easier to identify patterns and trends in data.
- Work on data analysis projects such as predicting customer behavior or analyzing sales data. This allows individuals to develop their skills.
Statistical programming languages
Knowledge of statistical languages is in high demand in the industry. The most-used languages are R and Python because they can easily manage the large data volumes generated by today’s businesses.
Programming languages make data transformation easy, and you can easily create new variables using existing ones or conduct mathematical transformations based on variable distribution. The languages boast libraries that assist in making predictive models.
To improve your programming skills:
- Practice regularly
- Enroll in online courses
- Be patient and take your time.
Visualization
Data visualization is critical in every industry today. It acts as the bridge between what business analytics professionals do and what clients need to know. Real-time visualization has come into the game, elevating the whole spectrum of visualization.
An aspiring business analytics expert needs to understand the importance of visualization and clearly understand which chart or graph is suitable for a particular data set. The most prominent visualization tools on the market include Tableau, Qlik Sense, and Power BI.
To improve your data visualization skills:
- Commit to easy-read layouts
- Try a new graph style
- Stop seeking the perfect data visualization tool or program and keep moving forward
Soft skills for business analytics roles
Different qualitative and personality skills make a technically efficient business analytics professional complete. These are some of the soft skills that a business analytics expert should possess:
Communication skills
Business analytics professionals should communicate complex data and analysis to different stakeholders in an understandable and actionable way. They should also listen to feedback and incorporate it into their analysis.
One can improve their communication skills through:
- Practicing data presentation
- Taking courses or workshops on communication skills
- Learning how to tailor communication to different stakeholders.
Business acumen
This refers to knowing the business context in which data analysis is conducted. Professionals working in business analytics need to understand the business objectives, industry trends and competitive landscape. They should also be able to identify opportunities for development and growth.
Here is how to improve business acumen:
- Learn about the company and industry in which you are working.
- Take part in cross-functional projects and teams.
- Develop a strategic mindset by reading books or taking courses on strategy.
Attention to detail
This is a vital skill for business analytics professionals. They must identify and correct data errors and develop appropriate recommendations. Attention to detail ensures that the analysis is accurate and the provided insights are reliable.
One can improve attention to detail by:
- Developing good habits, such as reviewing data thoroughly and maintaining accurate records.
- Using tools to ensure that analysis is accurate and reliable.
- Seeking feedback from stakeholders to identify areas where attention to detail can be enhanced.
Time management skills
Business analytics professionals must manage their time effectively to deliver projects on time and meet deadlines. They must also prioritize tasks and manage their workload to ensure that they meet the business’s needs.
One can improve time management skills by:
- Using time management tools such as to-do lists, calendars, and project management software to manage deadlines and tasks effectively.
- Break down complex projects into smaller, more manageable tasks to make it easier to manage time effectively.
- Develop good habits, such as setting priorities, avoiding procrastination and managing distractions to maximize productivity.
How to become a good business analyst
To become an excellent business analyst, you need the right technical and soft skills and should approach new problems with curiosity and a positive attitude. The skills people talk about are just the baseline requirements for being a business analytics expert. One needs to be curious and inquisitive, always seeking to understand new problems and find solutions. It is also important to develop a problem-solving attitude and not just rely on existing tools and methods.
Finally, it is important to stay up to date with industry trends and new technologies, such as machine learning algorithms, to gain a competitive edge in the business analytics field. The most successful business analytics professionals are always looking for ways to improve their skills and develop new ones. Taking courses, attending workshops and conferences, and talking to others in the field are just some of the ways you can stay up to date with industry trends and hone your skills as a business analyst.
