week 7 - data analytics + business intelligence Flashcards
what is meant by data analytics?
process of collecting, cleaning, inspecting, transforming, storing + querying data. This is relied on heavily by business intelligence.
what are the purposes of data analytics?
- convert + clean raw data into actionable insights.
- identifies past patterns + uses this to forecast future occurrences.
- carries out data mining tasks + algorithm development.
- preserves analysts + computer programmers who have a technical focus.
what is meant by business intelligence?
combines architectures, tools, databases, analytical tools, application + methodologies that convert unprocessed data into valuable insights.
what are the purposes of business intelligence?
- supports decision making using insights.
- looks back at the past + uses this to inform future strategy.
- used by leadership teams + non technical personnel.
- relies on clean dashboards, reporting + other monitoring techniques to relay insights in a clear + easily consumable way.
what are the characteristics of changing business environments?
- increased hardware, software + network capabilities.
- analytical support, group communication + collabs.
- overcoming cognitive limits in processing + storing info.
- improved data + knowledge management.
- managing giant data warehouses + big data.
- anywhere, anytime support.
how does business intelligence give a business a competitive advantage?
- improved decision making: data driven insights enable businesses to anticipate market trends.
- personalisation + customer experience: ai powered recommendation systems tailor user experiences.
- operational efficiency: predictive maintenance prevents costly equipment failures.
- fraud detection + risk management: ai driven analytics identify suspicious transactions + fraud patterns.
what is an example + the impact of improved decision making for giving a business competitive advantage?
Example: retailers use BI to analyse customer purchase patterns.
Impact: reduces stockouts + excess inventory costs.
what is an example + the impact of personalisation + customer experience for giving a business competitive advantage?
Example: netflix + amazon leverage bi to suggest relevant content/products.
Impact: increase customer engagement + sales conversions.
what is an example + the impact of operational efficiency for giving a business competitive advantage?
Example: manufacturers use sensors to detect issues before breakdowns.
Impact: reduces downtime + maintenance costs.
what is an example + the impact of fraud detection + risk management for giving a business competitive advantage?
Example: banks use bi to flag unusual activity in customer accounts.
Impact: improves security, minimises financial losses + enhances compliance.
what is a database?
organised collection of data, stored electronically for easy retrieval.
what is the importance of databases?
stores + manages large scale business data, enables fast retrieval of structured info, allows for data driven decision making.
what are the types of databases in analytics?
- relational database sql
- non relational database nosql
what is a relational database (sql)?
structured way of storing data in tables where relationships exist between data points, it follows the relational model.
what are the features of relational databases?
- data is stored in tables (relations).
- each row is a record (tuple).
- each column is an attribute (field).
- uses primary + foreign keys to establish relationships.
what are non-relational databases?
flexible data storage system that does not use structured tables + fixed schemas.
what are non-relational databases designed for?
- scalability.
- performance.
- handling large volumes of unstructured data.
what is meant by data quality?
a measure of how well data meets its intended purpose. poor data can lead to incorrect decisions.
what are the common issues regarding real world data?
- missing values.
- duplicates.
- outliers.
- inconsistent formats.
what are the key dimensions of data quality?
- accuracy.
- completeness.
- consistency.
- timeliness.
- validity.
what is meant by big data?
high volume, velocity + variety info assets that demand cost-effective, innovative forms of info processing for enhanced insight + decision making.
what do those 3 v’s mean in the definition of big data?
- volume: size of data.
- velocity: how fast new data is generated.
- variety: many different forms (text, image, audio, video).
what is meant by a data lake?
a centralised storage system that holds large amounts of data in its original format.
moves the burden of data cleaning + integration to later stages.
what is hadoop?
an open source framework that’s popular for distributed storage + parallel processing of massive amounts of data, spreading the data over a large cluster of machines.
