Glossary

• A

• Ad Hoc Analysis

  Ad hoc analysis refers to the process of getting an answer to a single business query at a time. It allows users to dig deeper by asking a series of questions and getting answers one after the other. This lets... Read More

• Advanced Analytics

  Advanced analytics uses advanced tools beyond traditional BI to analyze large data sets, offering deeper insights for better decision-making. These techniques help organizations predict user behavior and make better decisions across the enterprise. Read More

• Amazon Redshift

  Amazon Redshift is a popular data warehouse service made for the cloud. Enterprises use it to store their growing business data in order to perform analysis using their existing BI tools and standard SQL. Read More

• Amazon S3

  Amazon Simple Storage Service (Amazon S3) is an object storage service enabling web-scale computing. It is a scalable, high-speed, web-based cloud storage service designed for data storage and archiving, application hosting for deployment, installation and management of web apps, software... Read More

• Attributes

  Attributes are individual pieces of information that describe characteristics of a dimension. Each attribute is linked to one or more columns in a dimension table and helps define how data can be grouped, filtered or analyzed. Read More

• B

• Big Data Analytics

  Big data analytics helps businesses examine large and diverse datasets. It uncovers useful patterns, trends and relationships in the data. These datasets come from various sources like websites, apps, sensors and more. Together, they offer a detailed view of how... Read More

• Business Intelligence

  Business Intelligence (BI) uses tools and methods to turn everyday business data into useful insights. Users no longer have to review long reports manually. BI provides a faster and more organized way to understand what's happening. Read More

• C

• Caching in Semantic Layer

  Caching means storing copies of data in a temporary location. This helps speed up future requests for the same data. In a semantic model, the results of frequently run queries are saved. These results are stored based on the meaning... Read More

• Calculated Measures

  Calculated measures are formulas that return results on aggregated data based on the current context. Read More

• Cardinality

  Cardinality is the term used to define the uniqueness of data values included in a specific column of a database table. It can refer to two things in databases– Read More

• Chart Definition

  A chart is a graphical representation intended to organize and represent a set of numerical or qualitative data to make data visualization easier to understand. Charts enable slicing, dicing and drilling-down of enterprise data so that users can examine it... Read More

• Cloud Analytics

  In this virtual expanse, data is no longer confined to isolated silos but is a dynamic force full of valuable insights waiting to be uncovered. Cloud analytics plays a pivotal role in this transformation by offering scalable, efficient, and accessible... Read More

• Cloud Data Platform

  Cloud data platforms are the modern means of data management. They let users store, access and analyze enterprise data via the cloud. As data volumes increase, enterprises find it difficult to store and manage their data securely using the traditional... Read More

• Cloud Data Warehouse

  A cloud data warehouse is a database solution that serves as a central repository of information for analytics, scale, and ease of use and is delivered as a managed service in a public cloud. Read More

• Cloud Migration

  Cloud Migration is the process by which organizations move some or all of their data infrastructure, applications and IT processes from legacy data centers to the cloud. Read More

• Customer Journey Analytics

  Customer journey analytics involves collecting and analyzing data related to customer behaviour. This analysis happens across multiple touchpoints and channels. The goal is to understand how customer actions affect business outcomes. Read More

• D

• Data Annotation

  Data annotation is the process of adding metadata, such as labels, tags or attributes to raw data, making it understandable for machine learning models. Think of this process as the backbone of computer vision models to help them accurately interpret,... Read More

• Data Architecture

  Over the past decade, data has grown rapidly. It's expected to reach 181 zettabytes by 2025. This creates big opportunities for smart, data-driven decisions. But many businesses still fall short. They have the tools, but not the right infrastructure. Less... Read More

• Data Catalog

  In today's data-driven landscape, businesses are inundated with vast amounts of data from various sources. Effectively managing, analyzing, and deriving insights from this data is critical for making informed decisions and gaining a competitive edge. This is where a data... Read More

• Data Drilling

  Business intelligence is about turning raw data into actionable insights. This leads to better decision-making. It also improves efficiency and helps organizations understand their operations more deeply. In most cases, data is aggregated in the initial reports. This simplifies the... Read More

• Data Fabric

  Data fabric is a data architecture approach that automates data management functionalities to offer a unified view of all databases and data assets. It simplifies data access by connecting organizational data and reducing complexities of data storage architecture across multiple... Read More

• Data Integration

  Data integration is the process of bringing together scattered and unorganized enterprise data. It creates a clear and unified framework. This approach makes sure that the information is accurate and easy to access. This is important for both operations and... Read More

• Data Lakehouse

  A data lakehouse is a data management system that combines the features of a data warehouse and a data lake. It accelerates data processing and enables advanced analytics. At the same time, it helps reduce costs. Read More

• Data Lineage

  Data lineage tracks how data flows through an organization. It records and visualizes how data flows within an organization. It shows where the data originated. It also reveals what transformations the data went through. Finally, it indicates where the data... Read More

• Data Mart

  Data mart isn't a new concept; it has been around for decades. With growing data volumes, businesses are facing several issues. These include data silos, inadequate data governance and lack of data security. Data silos block seamless access and collaboration.... Read More

• Data Modeling

  Data modeling is the process of defining and analyzing different data types and the relationships between them. It involves creating a structured representation of data. This structure allows for the physical organization of data to support analytical queries. The main... Read More

• Data Monetization

  Data includes all the information and knowledge businesses rely on. It serves as the foundation for how modern organizations operate and grow. Monetizing this data is a key strategy. It helps unlock new revenue streams and explore innovative opportunities. Read More

• Data Normalization

  Data normalization is the process of reorganizing data into a structure and format that's consistent throughout the database, which makes it more accessible for users to query and analyze. The storage system of the data is made logical with normalization... Read More

• Data Refresh

  Data refresh is the process of updating or replacing data to reflect the latest available information in the overall enterprise environment. It ensures that BI platforms and analytical systems consistently mirror changes in the source data to maintain accuracy and... Read More

• Data Science

  Data science is the study of how to use tools and methods to find useful information in raw data. It uses machine learning to understand unstructured data and extract insights. Read More

• Data Storytelling

  When presented in massive quantities, data can be hard to digest. Therefore, data owners need to create a sequential flow of information while presenting the data. However, tabular data might still not be straightforward enough, requiring assistance from graphical and... Read More

• Data Streaming

  Data streaming is becoming the driving force behind modern apps and businesses. It enables a continuous flow of data from multiple sources. These include sensors, social media feeds, and market data. The data is processed and analyzed in real time.... Read More

• Data Transformation

  Data transformation is the process of changing the format and structure of data. The goal is to make the data compatible with a target system. While usability is the primary goal, transformation also adds value in other ways. Read More

• Data Vault

  Data vault refers to a data modeling technique designed for enterprise data warehousing to handle large-scale and complex data from disparate sources in a way that provides flexibility, scalability and adaptability. The concept was first introduced by Dan Linstedt in... Read More

• Data Virtualization

  Data virtualization works as an abstraction layer for the organization 's data assets. This involves aggregating data on-demand from various sources. Data virtualization reduces the reliance on traditional ETL (Extract, Transform, Load) procedures. It enables users to retrieve and analyze... Read More

• Data Visualization

  Data visualization is the use of visuals like charts and graphs to show information. It helps people quickly find trends and patterns in large sets of data and make better decisions. Read More

• Data Warehouse

  A data warehouse is a system used to store and manage data. It combines data from different sources into a structured format. This creates a single source of truth for the entire organization. Read More

• Data Wrangling

  Data wrangling is the process of converting and organizing raw enterprise data into a usable format. It is essential for enhancing the quality and suitability of the data so that it can be consumed for analytics. Read More

• Data-Driven Insights

  Data-driven insights are clear takeaways gained by examining raw data. They help companies spot patterns in data and understand the reasons behind them. These insights turn complex information into useful guidance for smarter decisions. Read More

• Dax Queries

  Data Analytics Expressions (DAX) is a formula expression and query language. It is designed for working with tabular models. It provides specialized syntax for querying and analysis. It is mainly used in Power BI, Excel Power Pivot and SQL Server... Read More

• Delta Lake

  Delta Lake helps organizations solve data lake and warehouse challenges. It offers scalability, flexibility and governance. It is an open-source layer for storage and management. It converts raw data in a data lake into a structured table format using Apache... Read More

• E

• Elasticity

  Elasticity means a system can automatically adjust resources based on current demand. Tools monitor the workload and add or remove resources as needed. Read More

• Enterprise Business Intelligence

  Enterprise BI refers to the deployment of BI in large enterprises to analyze data. The goal is to find business problems that need attention. Solving them helps speed up decision-making and makes it more informed. This also gives a clear,... Read More

• Excel

  Excel is a part of the MS office suite used to create worksheets and record data in the form of tables. Businesses use Excel to organize their data into something useful. They use it to perform business analysis, reporting, etc... Read More

• F

• Fact Table

  A fact table is a table that contains all the business information used in the dimensional model as a central table in a star schema of a data warehouse. A fact table stores fields that represent facts. Read More

• Financial Analytics

  Financial analytics examines historical data to assess a company's financial health. It helps businesses reduce costs, increase profits and plan stronger budgets. Companies can spot patterns and trends in their data. This helps them track profitability, cash flow and overall... Read More

• H

• Hierarchical Database Model

  In today's digital age, data is growing faster than ever before. Managing and storing this data effectively is crucial. It's the only way for organizations to stay ahead of the competition. To achieve this, they need structured database models. These... Read More

• K

• KPI Software

  Key Performance Indicators (KPIs) are measurable metrics that show how well things are going. Taken from the organization's core values, vision and mission, KPIs connect stakeholders' aspirations to what is really happening, making sure that activities are in line with... Read More

• M

• MDX Queries

  Multidimensional Expressions (MDX) help connect large data repositories to valuable business insights. As users learn how MDX works, they see it's more than just a query language. It unlocks a world of data-driven possibilities. Read More

• Medallion Architecture

  Organizations store massive amounts of data into their storage systems. In its raw form, this data isn't useful. It needs to be refined, structured and processed to yield valuable insights. This means cleaning the raw data for accuracy. You'll remove... Read More

• R

• Risk Analytics

  Risk analytics refers to the techniques that measure and predict risk more accurately. Companies can now leverage the power of their business data thanks to big data growth. Enhanced computing capabilities and advanced analytics also play a key role. Read More

• S

• Self-Service Analytics

  Earlier, data and reports were restricted by the number of users and the high cost of analytics tools. So, the companies were mindful of providing access to data and reports. However, organizations are now more open to offering democratized access... Read More

• Single Source of Truth

  Users might face difficulties when the database systems are not organized. Their data is fragmented and not all employees are using the same data. To overcome this difficulty, businesses are opting a single source of truth model. Read More

• Snowflake Schema

  Used in data warehousing, a snowflake schema is a multi-dimensional data model in which dimension tables are further broken down into subdimensions to represent multiple levels of granularity. It can be seen as a step forward from star schemas. As... Read More

• Star Schema

  Star schema is a database model created with a central table containing facts and dimensional tables having descriptive details about the data's context. Facts and dimensions are created using foreign keys that define the relationships between these tables. Read More

• Supply Chain Management

  Supply chain management is about how goods and services flow. It includes getting raw materials and the manufacturing process. Finally, the product is delivered to the consumer. Read More

• X

• XIRR

  XIRR stands for Extended Internal Rate of Return. It is a financial metric used to calculate returns on investments when cash flows occur at irregular intervals. Unlike the standard IRR, which assumes all payments are spaced evenly over time, XIRR... Read More