Data Business Glossary

Big Data and Cloud Technologies

Big Data

Big data refers to extremely large and complex datasets that traditional data processing applications cannot adequately handle, typically characterized by high volume, velocity, and variety.

Business Advantage:

Big data approaches unlock value from information that would otherwise be too overwhelming to process. Companies harnessing big data typically discover 20-30% more optimizationopportunities than with traditional analytics, identify subtle patterns invisible in smaller samples, and create more resilient forecasts by incorporating a wider range of variables.

Hadoop

Hadoop is an open-source framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.

Business Advantage:

Hadoop dramatically reduces the cost of large-scale data processing. Organizations using Hadoop typically reduce data storage and processing costs by 40-60% compared to traditional enterprise solutions, scale analytics capabilities more economically as data volumes grow, and retain more historical data for
analysis without proportional cost increases.

Spark

Spark is a unified analytics engine for large-scale data processing, designed for both batch and real-time data processing with capabilities for SQL, streaming, machine learning, and graph processing.

Business Advantage:

Spark accelerates complex analytics workflows. Businesses using Spark typically process data 10-100x faster than with traditional frameworks, enable more interactive analysis of large datasets, and unify disparate processing needs under a single platform, reducing technical complexity and maintenance costs.

NoSQL

NoSQL encompasses a variety of database technologies designed for specific data models with flexible schemas, offering simpler scaling and performance benefits for certain use cases.

Business Advantage:

NoSQL databases excel at handling data types and volumes that challenge traditional databases. Organizations using appropriate NoSQL solutions typically improve application response times by 30-50% for specific workloads, scale more cost-effectively to handle growth, and accelerate development by better matching data storage to application needs.

Data Lake
House

Data Lake House

A data lake house combines elements of both data lakes and data warehouses, providing the flexibility of data lakes with the management features and performance of data warehouses.

Business Advantage:

Lake house architectures give you both flexibility and control. Companies implementing lake house approaches typically reduce total data infrastructure costs by 20-40%, accelerate time-to-insight by eliminating movement between separate systems, and create more adaptable data environments that evolve with changing business needs.

Cloud Computing

Cloud computing delivers computing services—including servers, storage, databases, networking, software, and analytics—over the internet, offering faster innovation, flexible resources, and economies of scale.

Business Advantage:

Cloud approaches transform IT from capital expense to operational expense. Organizations moving to cloud typically reduce infrastructure costs by 20-40%, accelerate new project implementation by 30-50%, and create more resilient operations with built-in disaster recovery capabilities that would be prohibitively
expensive to duplicate on-premises.

Data as a Service (DaaS)

Data as a Service provides data access on demand via cloud-based platforms, enabling organizations to access and use data without having to build and maintain their own data infrastructure.

Business Advantage:

DaaS eliminates the need to recreate commonly needed datasets. Businesses using DaaS typically reduce time-to-insight for new projects by 40-60%, access specialized data that would be impractical to collect independently, and make better-informed decisions by incorporating external context beyond their own operational data.

Infrastructure
as a Service
(IaaS)

Infrastructure as a Service (IaaS)

Infrastructure as a Service provides virtualized computing resources over the internet, including servers, storage, and networking, allowing businesses to avoid investing in physical hardware.

Business Advantage:

IaaS creates an agile foundation for your technology needs. Organizations using IaaS typically reduce capital expenditure by 30-50%, scale resources up or down based on actual needs rather than worst-case projections, and accelerate deployment of new capabilities by eliminating hardware procurement delays.

Platform as
a Service (PaaS)

Platform as a Service (PaaS)

Platform as a Service provides a platform allowing customers to develop, run, and manage applications without dealing with the complexity of building and maintaining the underlying infrastructure.

Business Advantage:

PaaS accelerates application development and deployment. Companies using PaaS typically reduce development time by 30-50%, decrease maintenance overhead by leveraging platform-managed components, and create more standardized applications that are easier to support and enhance over time.

Software as a Service (SaaS)

Software as a Service delivers applications over the internet on a subscription basis, eliminating the need for organizations to install, maintain, and update software locally.

Business Advantage:

SaaS eliminates the burden of software maintenance. Organizations using SaaS typically reduce total cost of ownership by 20-40% compared to on-premises alternatives, access new features immediately without disruptive upgrade projects, and create more flexible work environments where employees can access tools from anywhere.

Serverless Computing

Serverless computing is a cloud execution model where the cloud provider dynamically manages the allocation of machine resources, charging only for the actual resources used to run applications rather than pre-purchased capacity.

Business Advantage:

Serverless approaches align costs directly with value creation. Businesses using serverless computing typically reduce infrastructure costs by 50-80% for variable workloads, eliminate capacity planning exercises that inevitably lead to either waste or shortages, and focus developer time on creating business value rather than managing infrastructure.

Microservices

Microservices is an architectural approach where applications are built as a collection of small, independent services that communicate over well-defined APIs, each focused on doing one thing well.

Business Advantage:

Microservices create more adaptable technology ecosystems. Organizations adopting microservices typically accelerate feature delivery by 30-50% through independent deployment capabilities, improve system resilience by containing failures to specific services, and enable teams to evolve different parts of the system at different rates based on business priorities.

Containers

Containers are lightweight, standalone, executable software packages that include everything needed to run an application: code, runtime, system tools, libraries, and settings.

Business Advantage:

Containers eliminate "it works on my machine" problems. Companies using containerization typically reduce environment-related issues by 40-60%, improve resource utilization by 20-40% through higher density, and accelerate deployment frequency by creating consistent environments across development and production.

Data Fabric

Data fabric is an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems.

Business Advantage:

Data fabric approaches simplify increasingly complex data landscapes. Organizations implementing data fabric architectures typically reduce integration costs by 30-50%, accelerate new use case implementation by leveraging reusable data products, and create more resilient data flows that adapt to changing source systems with minimal disruption.

Data Mesh

Data mesh is a decentralized approach to data architecture where domain-specific teams own and serve their data as products, with centralized governance ensuring interoperability and quality.

Business Advantage:

Data mesh aligns data ownership with business expertise. Businesses adopting data mesh typically accelerate time-to-value for domain-specific use cases by 40-60%, improve data quality through clear ownership accountability, and scale data capabilities more effectively across large or complex organizations.

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