Applying Traditional Data, Big Data, BI, Traditional Data Science and ML

1. Data: It is defined as information stored in a digital format, which can then be used as a base for performing analyses and decision making.
2. Traditional Data: Data in the form of tables containing numeric or text values data that is structured and stored in databases which can be managed from one computer.
3. Big Data: on the other hand is a whole nother story and it coule be assumed by the name. It is a term reserved for extremely large data and it is not just humongous in terms of volume. This data could be in various formats. It can be structured, semi-structured or unstructured.
4. Volume: Big data needs a whopping amount of memory space typically distributed between mini computers. Its size is measured in terabytes Pedda butes and even exabytes.
5. Variety: Big data often implies dealing with images audio files mobile data and others.
6. Velocity: One’s goal is to make extracting patterns from it as quickly as possible. The progress that has been done in this area is remarkable outputs from huge data sets can be retrieved in real time. This means they can be extracted so quickly that a result could be computed immediately after the source data has been obtained.
7. Data science and analytics data science is a broad subject. It is an interdisciplinary field that combines statistical mathematical programming problem solving and data management tools.
8. Business intelligence analyse the past data that you have acquired. BI is the discipline you need for this.
9. BI includes all technology-driven tools involved in the proces of analyzing, understanding and reporting available past data. This will result in you having reports or dashboards and will help you on your way to making an informed strategic and tactical business decision. This part of the process is worth your time. You can extract insights and ideas about your business that will help it grow and give you an edge of your competitors giving you added stability. Business intelligence means understanding how your sales grew and why did competitors low market share. This is waht BI is all about udnerstanding past business performance in order to improve future performance.
10. Traditional Methods: It also called traditional data science or machine learning to develop an idea of what will hapen in the future. Traditional methods according to our framework are a set of methods that are derived mainly from statistics and are adapted for business.
11. Traditional methods: they are perfect for forecasting future performance with great accuracy. Regression, cluster and faster are belong to traditional methods.
12. Machine learning: It through mathematics. A significant amount of computer power in applying AI the machine is given the ability to predict outcomes from data without being explicitly programmed to smell is all about creating algorithms that let machines receive data perform calculations and apply statistical analysis in order to make predictions with unprecedented accuracy.