Earlier this year, we took a look at the importance of using Business Intelligence in a business setting, as well as 6 critical steps to becoming a data-driven business. We had quite a bit of interest and feedback from these articles, which prompted our team to outline some key terminology that readers should be aware of.
Before you begin your venture into the world of data analytics, it is crucial for you to know and understand these key terms.
Metric: A quantifiable measure used to monitor, track, and compare a specific process.
KPI (Key Performance Indicator): A metric that a company uses to gauge its performance towards certain long and/or short-term business objectives. Do note that all KPIs are metrics but not all metrics are KPIs.
Dashboard: A mainframe that visually tracks, analyzes and displays views of KPIs, metrics and key data points relevant to a particular objective or business process.
Forecasting: An algorithmic way of predicting future data based on existing data.
ETL (Extract, Transform, Load): The process of extracting the data from the data source(s), transforming it to the proper structure, and loading it into the analysis system of choice.
Data type: A data type defines what kind of value a column can hold: integer data, character data, date and time data, binary strings, and so on.
Database: A database is a collection of information that is organized to allow users to easily access, update and manage the information.
Data model: A data model defines how data is connected to each other and how they are processed and stored inside the system. The data model should capture all the entities, relationships and ultimately the flow of data.
Data governance: The overall management of the availability, usability, integrity, consistency, and security of data used in an organization. Data governance includes the people, process and information technology required for creating consistent and appropriate handling of an organization’s data throughout the business.
Big data: Big data refers to sets of data, both structured and unstructured, that are so huge and intricate that traditional data processing software lacks the ability to deal with them.
Drill-down: A method of exploring multidimensional data by going from one level of detail to the next, depending on the granularity of the data.
Query (computing): A query is a request for data or information from a database. Most queries start with a simple business question such as ‘How many clients do I have that spent above $x amount during the last 2 years’, which is then transformed into a machine-readable format (such as SQL).
Insights: Insights are the value obtained through the use of data analytics. Insights can be gained through data analytics to help businesses identify areas of opportunity and growth.
Structured Query Language (SQL): SQL is a standardized language for managing, housing, transforming, and retrieving data from databases.
Now that you’ve read and understood these key terms, it’s time to begin your venture into the world of data analytics. If you are considering a data-driven approach to your business, Enkel can help you propel forward with confidence. Contact us today to learn more about our accounting and data analytics service.
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