data analytics final studying

what is data analytics?

investigating raw data of various types to uncover trends and correlations and answer questions

descriptive analytics

uncovers historical trends in data sets

predictive analytics

understanding, predicting, and planning for future business outcomes

prescriptive analytics

used to determine best courses of action

data ecosystem

the tools and systems used to collect, store, analyze, and understand data

5 steps of data life cycle

sensing (identify what data should be collected), collecting (collect data from sources), wrangling (convert raw data to user-friendly format), analysis (examine the data), store (derive conclusion and store the data)

to make data driven decisions organizations should invest in…

data proficiency (ability to understand, analyze, and interpret data), agility in analytics (quickly analyze the data and adapt new info), and build a data driven culture (the mindset of decisions are guided by data rather than assumptions)

6 steps to create data driven decisions

ask (what questions need to be answered or what problem should be solved), prepare (collect data, store it, and prepare for analysis), process (cleanse the data and ensure it is ready for analysis), analysis (analyze data to find patterns, trends, and relationships), share (with the audience), act (a decision must be made)

three data analyst tools

spread sheets (excel and good sheets), database and query language, and data visualization tools

advantages of SQL

popular, previous coding experience is not needed, reliable, handles large volume of data, and processes queries quicky and reliably

disadvantages of SQL

SQL databases could be complex to manage and set up, can’t process changes in real-time, can’t handle unstructured data

design elements that lead to misleading data visualization

truncated graphs (cutting off y-axis), using un-uniformed scale for pictogram, using too many variables in chart can distract audience, cherry picking data, using misleading colors, most popular charts

What are the data formats used in datasets?

primary data, secondary data, internal data, external data, continuous data, discrete data, qualitiative data, quantitative data, nominal data, ordinal data, structure data, unstructured data