Business Analytics and Big Data¶

Business Analytics¶

Descriptive analytics: uses data to understand past and present
- Example in healthcare: Average number of patients readmitted in emergency care in a period -- Link to Key Performance Indicators
Predictive analytics: analyzes past performance to predict future
- A four-step process:
  1. Identify the problem
  2. Explore historical data (What descriptive analytics has to say)
  3. Build and validate a model based on the data
  4. Deploy the model on new data to make predictions (with probabilities of accuracy).
- E.g. Classify patients who are at high risk for a condition such as diabetes or coronary artery disease.
Prescriptive analytics: uses optimization techniques to come up with best recommendations
- predictive analytics --helps determine what might happen, prescriptive analytics helps determine the best course of action
- E.g. How many beds to allocate for a certain category of patients during a certain period (E.g. Flu season)

![[Screen Shot 2024-05-06 at 08.41.12.png]]

Canned reports: Provide regular summaries of information in a predetermined format.
Ad hoc reporting tools: Puts users in control so that they can create custom reports on an as-needed basis by selecting fields, ranges, summary conditions, and other parameters.
Dashboards: Heads-up display of critical indicators that allows managers to get a graphical glance at key performance metrics.
Online Transaction processing (OLTP): Takes data from standard relational databases and uses the data to facilitate transactions by large numbers of people, typically over the internet.
Online analytical processing (OLAP): Takes data from standard relational databases, calculates and summarizes the data
- dynamic pricing: Changing pricing based on demand conditions
- Much more unstructured data being captured

data warehouse: a set of databases designed to support decision-making in an organization. It is structured for fast online queries and exploration. Data warehouses may aggregate enormous amounts of data from many different operational systems.
data mart: a database focused on addressing the concerns of a specific problem (e.g., increasing customer retention, improving product quality) or business unit (e.g., marketing, engineering).
Walmart - A Data-driven Value Chain
- Source of competitive advantage is scale.
- Efficiency starts with a proprietary system called Retail Link.
  - Retail Link—records a sale and automatically triggers inventory reordering, scheduling, and delivery.
  - inventory turnover ratio: Ratio of a company’s annual sales to its inventory.
- Back-office scanners keep track of inventory as supplier shipments come in.
- Facilitates just-in-time inventory management
- Data-Driven Prediction
- Walmart shares sales data only with relevant suppliers

Big data: a collection of data sets so large and complex that it becomes difficult to process using regular database management tools or traditional data processing applications
4+1V to characterize big data: Volume, Velocity, Variety, Veracity, Value ![[Screen Shot 2024-05-06 at 10.13.11.png]]
Data mining: The process of using computers to identify hidden patterns in, and to build models from, large datasets
Big Data Analytics goes one step forward by examining the raw data with the purpose of drawing conclusions (making inferences) about that information.
The ultimate objective of both is to help make better decisions (future)
E.g. Big Data Helps Fix Boston’s Potholes
- Crowdsourcing approach

Conceptual Model (Outcome: ERD)
- Entity, attribute, relationship
  - Cardinality: the maximum number of relationship instances in which an entity can participate. (1, N)
  - Modality: Optional or Mandatory relationship (minimum number of relationship instances) (0, 1)
  - Resolving Many-to-Many Relationships
Logical Model (Outcome: Data dictionary)
- Conversion
- Normalization
  - PK: Each row in a table must be uniquely identified by the value of the Primary Key
  - FK: All values of foreign keys must exist as values in the parent table
  - Advantage: No redundancy, integrity, avoids anomalies (update, deletion, insert)
  - 1NF
    - There are no repeating or duplicate fields
    - Each record is uniquely identified by a primary key (courseid)
    - Each cell contains only a single value
  - 2NF
    - It is already in 1NF and all nonprimary key fields depend on the key
  - 3NF
    - 2NF is a pre-requisite
    - No non-key field depends upon another non-key field (all non-key fields depend only on the primary key).
Physical Database (Outcome: Database)