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Business intelligence like any other industry has its terms and idioms that everyone might not be familiar with. Such terms are widely used in business intelligence to convey unique ideas and directions for a smooth functioning of the organization. Business Intelligence jargons are important for people to understand certain directions and perform their duties more efficiently. Understanding the basic BI terms help individuals to improve in their corporate occupation.
A data silo is an independent source of data that is not connected to any other data sources. Businesses generate lots of data from various sources like simple excel files, on-premise databases, social media profiles and web services. Different businesses have different data silos with different departments like sales, finance, marketing etc in the same organization. They all use different ways to collect data and store them separately. BI makes use of data obtained from data silos to resolve queries and join it with other data from various sources or transfer data from one source to another.
Data warehouse is a database in which the data is extracted from different sources. It brings together all the data together to start processing and examining data by the business intelligence method for the smoothing functioning of the company. It keeps the copies of all the current and past data so that they can be used for any past reference. Hence, it can be used to make analysis faster and easier while not interfering with the original data source. As the data is extracted from sources and is stored in the warehouse, the data can be cleaned and transformed whenever it is required to make it more compatible.
ETL stands for extract, transform and load. Its main job is to extract data from different sources, transform it to some other place and load the data for future reference. It solves three major issues i.e., ETL enables companies to bring together all the data together in one place like a warehouse. Second, ETL helps to transform complex formats like JSON, CSV, XML into simple formats for better analysis and understanding of the people. Third, it helps in detecting and fixing errors that might exist in the source.
RDBMS stands for relational database management system. RSBMS is a software used to manage and look after relational databases like MySQL, SQL Server and PostgreSQL for example. Data warehouses are relational databases, so it requires RDBMS for better management. These databases are made up of different datasets called tables. Each table has a relationship with one another resulting in data fields containing the same information called joining keys.
SQL stands for structured query language that communicates with relational databases. In BI SQL is widely used for solving queries regarding databases and then aggregating and filtering data according to its need. Most BI tools have SQL engines to carry out a task very smoothly. Each RDBMS, MySQL, SQL server etc have their SQL engine slightly different from each other in terms of syntax but over similar to each other.
KPI stands for key performance indicator. They are BI metrics is used to supervise the overall performance of the company, whether they could achieve the objectives or not. They tend to focus more on key areas like marketing, finance, sales or website traffic. Its goal is to determine and explain the ways and strategies of how a company will progress and meet its marketing and business goals. It helps the organization to understand whether they are headed in the right direction or not.
Dashboards are the end product of the business intelligence process. These are certain single screen reports that provide critical and metrics information, guide decisions and better navigate the surrounding landscape. It plays a major role in business performance management. A BI dashboard is used to determine things like revenue, stock levels, social media engagement, competitive analyses and take instant action immediately streamlining the workflow and properly purposing resources.
The database is an organization's collection of data and information like images, numeric, scripts or texts stored, managed, updated and accessed electronically through computers and servers. In business intelligence, databases include systems like Microsoft dynamics, Excel, CRM, salesforce etc which contains data records like sales transactions, products catalogues, inventories and customer profiles. This information is stored in the form of a database.
Big data are data that are in large volume and has a variety of information assets extracted from different sources like social media, blogs, sensors, IoT devices and much more that demand cost-effective and innovative information processing through BI to enhance insight, decision-making and process automation. This large amount of data provides real commercial opportunities in marketing, product development and pricing.
DAX stands for data analysis expressions that provide syntax for query analysis services for Microsoft PowerPivot, PowerBI, SQL server analysis services. DAX is also used in Excel formulas designed to work with relational data and perform dynamic aggregation. Integer, real, currency, string, Boolean, date and BLOB (binary large object) are 7different data types that DAX can compute. It is designed in a way that is simple and easy to grasp.
