Glossary
Short definitions of terms you will come across in data projects and in our articles.
- BI (business intelligence)
Tools and processes that turn data into reports and dashboards for decision-making.
Related service: Analytics & BI
- Business glossary
Agreed definitions of business terms and metrics: what exactly counts as an "active customer" or "revenue". The basis for consistent numbers across reports.
Related service: Data Quality & Data Governance
- Dashboard
A screen with key metrics and charts that gives the picture on a topic in one place and refreshes automatically.
Related service: Analytics & BI
- Data accuracy
How well values match reality: the correct price, the right address, the actual shipping date.
Related service: Data Quality & Data Governance
- Data catalog
A description of a company's datasets: where they live, what they contain, who owns them and how far they can be trusted. It helps people find the right data quickly.
Related service: Data Quality & Data Governance
- Data completeness
Whether the data contains all the required records and values. For example, the share of customers without a phone number or orders without an amount.
Related service: Data Quality & Data Governance
- Data consistency
Whether the same data matches across systems and reports. An example of inconsistency: monthly revenue differs between the CRM and the accounting system.
Related service: Data Quality & Data Governance
- Data drift
A change in input data or patterns over time that makes a model err more often. It is tracked through monitoring.
Related service: ML & Advanced Analytics
- Data governance
A system of rules, roles and processes that defines who is responsible for data and how it is described, checked, stored and used.
Related service: Data Quality & Data Governance
- Data lake
Storage for large volumes of data in its original form, including files, logs and unstructured data.
Related service: Data Engineering
- Data lineage
The path data takes from source to report: which systems it came from and what transformations it went through. It helps find the cause of a wrong number quickly.
Related service: Data Quality & Data Governance
- Data mart
A prepared dataset for a specific task or department, such as sales or finance. Reports are built on data marts rather than on raw data.
Related service: Analytics & BI
- Data maturity
An assessment of how systematically a company works with data: quality, infrastructure, processes, skills and the use of data in decisions.
Related service: Data Strategy & Audit
- Data owner
A business leader accountable for a dataset: approves quality and access rules and resolves disputes.
Related service: Data Quality & Data Governance
- Data pipeline
An automated chain of steps that regularly moves data from sources to the warehouse, data marts and reports.
Related service: Data Engineering
- Data quality
The degree to which data is fit for its purpose: reports, decisions, automated processes. It is measured across several dimensions: completeness, accuracy, consistency, timeliness and uniqueness.
Related service: Data Quality & Data Governance
- Data steward
A specialist who looks after the quality of specific data day to day: investigates errors and maintains reference data and descriptions.
Related service: Data Quality & Data Governance
- Data strategy
A plan that links business goals to data initiatives: what to do, in what order, with what budget and expected return.
Related service: Data Strategy & Audit
- Data timeliness
How up to date data is at the moment it is used: whether stock levels are refreshed before the morning meeting, whether yesterday's sales made it into the report.
Related service: Data Quality & Data Governance
- Data uniqueness
The absence of duplicates: each customer, product or counterparty is represented by a single record.
Related service: Data Quality & Data Governance
- DataOps
Practices that make data work reliable and predictable: automated checks, load monitoring, change control and fast recovery from failures.
Related service: Data Engineering
- DWH (data warehouse)
A central database where data from different systems is loaded, cleaned and brought into a single shape for analytics.
Related service: Data Engineering
- ETL and ELT
Data loading processes: extract from the source, transform, and load into the warehouse. In ELT, data is loaded first and transformed inside the warehouse.
Related service: Data Engineering
- Forecasting
Estimating future values from history and external factors: demand, sales, staff or warehouse workload.
Related service: ML & Advanced Analytics
- KPI (key performance indicator)
A metric used to track progress toward a goal: revenue, margin, inventory turnover, repeat purchase rate.
Related service: Analytics & BI
- Lakehouse
An architecture that combines the low-cost storage of a data lake with the structure and easy querying of a data warehouse.
Related service: Data Engineering
- Machine learning model
An algorithm that finds patterns in historical data and applies them to new data: forecasts, classifies, recommends.
Related service: ML & Advanced Analytics
- MDM (master data management)
Practices and systems for maintaining a single reference of key entities — customers, products, counterparties — that all other systems take their data from.
Related service: Data Quality & Data Governance
- Metadata
Data about data: table structure, field descriptions, source, refresh time, owner.
Related service: Data Quality & Data Governance
- MLOps
Practices for putting models into production and running them: deployment, quality monitoring, retraining and version control.
Related service: ML & Advanced Analytics
- Orchestration
Managing how pipelines run: schedules, step order, dependencies, retries on failure and alerts.
Related service: Data Engineering
- Scoring
Estimating the probability of an event for each object: for a customer, the likelihood of churn or purchase; for an application, the level of risk.
Related service: ML & Advanced Analytics
- Self-service BI
An approach where business users build reports on prepared data themselves, without going to analysts every time.
Related service: Analytics & BI
- SQL
A query language for databases. It lets you select, join and aggregate data and is the main tool of analysts and data engineers.
Related service: Team Training