Analytics

/rɪsk əˈnæl.ə.sɪs/

noun — "figuring out what could go wrong before it actually does (and usually does anyway)."

Risk Analysis in information technology is the process of identifying, assessing, and prioritizing potential threats to systems, data, or business operations. It helps organizations understand the likelihood and impact of risks so they can implement controls, mitigation strategies, and contingency plans.

Technically, Risk Analysis involves:

/ˈpaʊər ˌbiː aɪ/

noun — "turning spreadsheets into flashy charts that make managers nod knowingly."

Power BI is a business analytics service by Microsoft that enables organizations to visualize, analyze, and share data in interactive dashboards and reports. It transforms raw data from multiple sources into insights, helping decision-makers understand trends, patterns, and performance metrics.

Technically, Power BI involves:

/ˈbɪznəs ɪnˈtɛlɪdʒəns/

noun — "turning raw data into charts that make executives look smart."

Business Intelligence (BI) is the practice in information technology of collecting, analyzing, and presenting data to help organizations make informed decisions. BI combines data warehousing, data analysis, reporting, and visualization to provide actionable insights into operations, performance, and strategic opportunities.

Technically, Business Intelligence involves:

/frɔːd dɪˈtɛkʃən/

noun — "catching sneaky transactions before they ruin your balance."

Fraud Detection is the process in information technology and cybersecurity of identifying and preventing unauthorized or deceptive activities, particularly in financial systems, e-commerce, or sensitive data environments. It relies on analyzing transaction patterns, user behavior, and system logs to flag suspicious activities before they cause losses or breaches.

Technically, Fraud Detection involves:

/ˈdeɪtə əˈnæləsɪs/

noun — "turning mountains of numbers into something that actually makes sense."

Data Analysis is the process in information technology and data science of inspecting, cleaning, transforming, and modeling data to extract useful insights, support decision-making, and identify patterns or trends. It forms the backbone of business intelligence, predictive analytics, and system optimization.

Technically, Data Analysis involves:

/əˈnɑːməli dɪˈtɛkʃən/

noun — "finding the needle in the data haystack before it ruins your day."

Anomaly Detection is a field in information technology and data science focused on identifying unusual patterns, outliers, or unexpected behaviors in datasets, systems, or network traffic. These anomalies may indicate errors, security breaches, fraud, system malfunctions, or rare but important events. Detecting anomalies helps organizations respond proactively to irregularities that could affect performance, security, or decision-making.

/ˌsɪɡnəl tuː nɔɪz ˈreɪʃi.oʊ/

noun … “how clearly a signal stands out from background noise.”

/lʊk-ɛm-ɛl/

n. “The language that teaches Looker how to see your data.”

LookML is a modeling language used in Looker to define relationships, metrics, and data transformations within a data warehouse. It allows analysts and developers to create reusable, structured definitions of datasets so that business users can explore data safely and consistently without writing raw SQL queries.

/ˈiː-tiː-ɛl/

n. “Move it. Clean it. Make it useful.”

ETL, short for Extract, Transform, Load, is a data integration pattern used to move information from one or more source systems into a destination system where it can be analyzed, reported on, or stored long-term. It is the quiet machinery behind dashboards, analytics platforms, and decision-making pipelines that pretend data simply “shows up.”

/ˈlʊk-ər/

n. “See the numbers, tell the story.”

Looker is a business intelligence (BI) and data analytics platform designed to turn raw data into actionable insights. It connects to databases, warehouses, and data lakes — for example, BigQuery, Cloud Storage, or SQL Server — allowing users to explore, visualize, and share data across organizations.