Business Analytics
If your business needs a piece of software or an application developing.
it’s not only the designers that you will have to work with. In fact, a person that you cannot afford to do without is a business analyst.
That’s not all business analysts do, though. In fact, perhaps their most crucial role is the bridge they provide between your business and those that are developing your software. A function that ensures effective communication steers the project to meet the specific goals of your business and ensures maximum efficiency of the process and the end results.
- Industry Analysis
- Technical Research
- Competition Analysis
This is because business analysis fulfill several crucial roles in the software development process. Such as helping to identify the problem, reviewing your competitors’ efforts, and analyzing the market in which you operate. Business analysts also record the entire process and create a formal specification detailing the needs of your company. A document that the developer will use as a blueprint for the concept creation.
The main components of a typical business analytics dashboard include:
- Data Aggregation: prior to analysis, data must first be gathered, organized, and filtered, either through volunteered data or transactional records
- Data Mining: data mining for business analytics sorts through large datasets using databases, statistics, and machine learning to identify trends and establish relationships
- Association and Sequence Identification: the identification of predictable actions that are performed in association with other actions or sequentially
- Text Mining: explores and organizes large, unstructured text datasets for the purpose of qualitative and quantitative analysis
- Forecasting: analyzes historical data from a specific period in order to make informed estimates that are predictive in determining future events or behaviors
- Predictive Analytics: predictive business analytics uses a variety of statistical techniques to create predictive models, which extract information from datasets, identify patterns, and provide a predictive score for an array of organizational outcomes
Data analytics is a broad umbrella term that refers to the science of analyzing raw data in order to transform that data into useful information from which trends and metrics can be revealed. While both business analytics and data analytics aim to improve operational efficiency, business analytics is specifically oriented to business uses and data analytics has a broader focus -- both business intelligence and reporting and online analytical processing (OLAP) fall under the data analytics umbrella.
Data science combines data analysis, statistics, machine learning, and related methodology in order to manage and understand the data deluge associated with the emergence of information technology. Data scientists are tasked with presenting digital information in a way that depicts its practical value in data-driven decision-making; however, they don’t typically endeavor to solve specific questions in the way that business analysts do when seeking out business analytics insights.