Intro to Data and Data Science

Imagine your boss wants to know what to do with the customer data to increase profits.. what do you do?

1. Analysis 2. Forecast

Imagine your boss wants to know the outgoing cost the firm in the next year... what do you do?

1. Gather relevant data 2. Prepare for analysis

Advanced Analytics Overview

1. all areas intertwine 2. not a strict representation of common accepted definitions

machine learning target

1. data 2. model (usage of bow) 3. objective function (calculate where) 4. optimization algorithm (improve performance)

balancing

the data is not skewed one way

Analytics

the science of fact-based decision making

time series analysis

A forecasting method that uses historical sales data to discover patterns in the firm's sales over time and generally involves trend, cycle, seasonal, and random factor analyses

regression analysis

A method of predicting sales based on finding a relationship between past sales and one or more independent variables, such as population or income

Unsupervised Learning

A type of model creation, derived from the field of machine learning, that does not have a defined target variable.

Supervised Learning

Category of data-mining techniques in which an algorithm learns how to predict or classify an outcome variable of interest.

Data

Facts and statistics collected together for reference or analysis

Deep Learning

Involves developing the tools of critical thinking and applying them to whatever challenges you encounter now and in the future.

Knowing which programming language is a huge advantage if you are supposed to be working with big data and/or machine learning?

Java

Data Science

Managing and analyzing massive sets of data for purposes such as target marketing, trend analysis, and the creation of individually tailored products and services.

Choose the best answer. Which software tool(s) are constantly being used across all five categories from our infographic?

Python and R

relational schema

The organization of a relational database as described by the database administrator.

Data Cleansing

The process of detecting incorrect or insufficient data

artificial intelligence (AI)

The science of designing and programming computer systems to do intelligent things and to simulate human thought processes, such as intuitive reasoning, learning, and understanding language.

Data Analytics

The science of examining raw data with the purpose of drawing conclusions about that information

From a data scientist's perspective, the solution of every task begins

with a proper dataset

KPI (Key Performance Indicator)

a measure of achievement that can be attributed to an individual, team, or department

business analysis

a review of the sales, costs, and profit projections for a new product to find out whether these factors satisfy the company's objectives

factor analysis

a statistical procedure that identifies clusters of related items (called factors) on a test; used to identify different dimensions of performance that underlie a person's total score.

cluster analysis

a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

Business Intelligence (BI)

analyzing, understanding, and reporting past data

ml engineer

applies state of the art computational models

text data

combination of letters, numbers and some symbols which form words and sentences

Which of the following columns from our infographic contain activities that are said to belong to the field of 'predictive analytics' and do not aim at explaining past behaviour? a. traditional data b. big data c. business intelligence d. traditional methods

d

Data Architect

design the way data will be retrieved, processed, and consumed

analysis

detailed examination of the elements or structure of something, typically as a basis for discussion or interpretation.

bi consultant

external BI analyst varied

data scientist

extracts knowledge from data by performing statistical analysis, data mining, and advanced analytics on big data to identify trends, market changes, and other relevant information

Big Data

extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

advanced analytics

focuses on forecasting future trends and producing insights using sophisticated quantitative methods, including statistics, descriptive and predictive data mining, simulation, and optimization

training your machine learning model

give final goal

database administrator

handles control of data and usually traditional

reinforcement learning

learning association between stimuli and reward receipt

In reinforcement learning, a reward system is being used to improve the machine learning model at hand. The idea of using this reward system is to:

maximize the objective function

class labeling

numerical, categorical

traditional methods

perfect for forecasting future performance for accuracy

bi analyst

perform analyses and reporting of past data

data analyst

prepares more advanced types of analyses

Data Engineer

process obtained data for analysis

Quantification

process of representing observations as numbers

bi developer

python + SQL to perform analyses designed for company

data shuffling

randomly mixing up data frame rows - prevents unwanted patterns - improves predictive patterns

Dealing with missing data

solve this before in the pre processing stage

traditional data

structured can be managed from one computer

traditional method example: UX

survey --> cluster analysis --> customer satisfaction, revenue

Machine Learning (ML)

the extraction of knowledge from data based on algorithms created from training data