BI Glossary

Learn some of the most important BI terms with our business intelligence glossary

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Ad-Hoc Analysis

Ad-hoc analysis is any business report or data analysis curated and created by users, as and when they need it. Ad-hoc analysis in business intelligence sits in stark contrast with the managed reports seen in the early days of business analytics.
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Advanced Analytics

Advanced analytics is an umbrella term for a group of high-level methods and tools that can help you get more out of your data. The predictive capabilities of advanced analytics can be used to forecast trends, events, and behaviors.
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Agile Analytics

Agile analytics is a paradigm for exploring data that focuses on finding value in a dataset by using a free-form adaptive approach to focus on agility.
analytical database
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Analytical Database

An analytical database collects historical data related to operations’ KPIs and metrics such as sales, performance, and inventory and is easily accessible.
Analytics Architecture
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Analytics Architecture

Analytics architecture is the way you structure your data, in both hardware and software layers, to define how users access and interact with it.
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Analytics-as-a-Service (AaaS)

Analytics as a Service typically offers cloud-based BI software that breaks down your data in a way that even non-techies gain insight and take action.
Application Analytics
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Application Analytics

Application analytics track the performance of web, mobile, and desktop applications to measure efficiency and success and monitor improvements and fixes.
Application-Based-Integration
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Application Delivery

Application delivery refers to the combination of services that companies must perform to provide functionality for the end-user or client. Application delivery uses a variety of platforms and technologies to create applications that are robust, available, and scalable.
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Application Lifecycle Management

Application lifecycle management is a set of tools and processes that oversee an application from inception to retirement and ensures smooth operations.
Application Modernization Featured Image
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Application Modernization

Application modernization is when a business updates its infrastructure or key product features to extract more value and align to current needs.
Automatic concurrency scaling glossary
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Automatic Concurrency Scaling

Automatic concurrency scaling is a feature of cloud-based data warehouses that automatically adjusts computational capacity to handle ever-changing demand.
Hadoop Logo
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Big Data and Hadoop

Hadoop handles big data that conventional IT systems cannot manage because the data is too big, arrives too fast, or comes from too many different sources.
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Big Data Basics

Big data analytics helps businesses to get insights from today’s huge data resources. This data can be examined to see trends, opportunities, risks, etc.
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Big Data Security

Big data security is the collective term for the measures and tools used to guard an organization's data and analytics processes from attacks and theft.
Business Intelligence
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Business Intelligence

Business intelligence is a data-driven process for analyzing and understanding your business so you can make better decisions based on real-time insights.
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Business Intelligence Architecture

Business intelligence architecture is the infrastructure that organizations use to define their data collection streams and information administration.
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Business Process Modeling

Business process modeling is the data visualization of companies’ workflows and business processes to extract insights and identify areas for improvement.
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Cloud Analytics

Cloud analytics refers to any BI or data analytics carried out in the cloud, which can be more versatile and cheaper than on-premise solutions.
cloud automation
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Cloud Automation

Cloud automation refers to the tools, activities, and processes used to reduce the manual oversight and management of cloud computing workloads and systems.
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Cloud Data Management

Cloud data management simplifies the communication of an organization’s data across the cloud and physical storage, and between private and public clouds.
Cloud migration
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Cloud Migration

Learn what Is Cloud Migration, what are the benefits, challenges, common strategies, and even a cloud migration checklist for your use.
Cognitive Computing | Sisense
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Cognitive Computing

Cognitive computing refers to the use of reasoning, language processing, machine learning, and human capabilities that solve problems and analyze data.
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Cohort Analysis

Cohort analysis is part of behavioral analytics that examines data from large sets and breaks it down into related groups to parse in a defined time frame.
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Columnar Database

A columnar database writes and reads data much more efficiently than row-oriented databases and can move very quickly to and from data sources.
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Contextual Data

Contextual data provides background information that organizations can use to understand customer behavior patterns and improve their experiences.
Sisense+Ovaledge Integration
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Dark Data

What is dark dataWhere is dark data generated fromWhat can you do with dark dataIs dark data good for analysis...
preparing data for analysis
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Data Blending

Data blending is combining multiple datasets to create a single, new dataset, which can then be processed or analyzed. Learn More!
Open source data mapping
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Data Cataloging

Data cataloging is the process of making an organized inventory of your data. The data catalog is what you’ll use to index where everything is stored.
Data Cleaning
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Data Cleaning

Data cleaning refers to preparing data for analysis by removing or modifying data that is incomplete, irrelevant, duplicated, or improperly formatted.
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Data Discovery

Data discovery is the process of uncovering relevant data insights and getting those insights to the business users who need them.
Exploratory vs Confirmatory Analysis
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Data Exploration

Data exploration is the process of analyzing a large data set in an unstructured way to uncover initial patterns, characteristics, and points of interest.
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Data Governance

Data governance ensures data is safe and handled in compliance with regulations, but also helps you gain value from all the information at your fingertips.
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Data Intelligence

Data intelligence refers to all the analytical tools companies employ to form a better understanding of their information in order to improve operations.
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Data Literacy

Data literacy is the skill set of reading, communicating, and deriving meaningful information from data, to put the information in context and tell a story.
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Data Mapping

As companies grow, data configurations become more elaborate. Data mapping is a way to establish a cohesive data model for a data-driven organization.
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Data Mart

A data mart is a subset of data stored within the overall data warehouse, for the needs of a specific team, section or department within the enterprise.
Data maturity glossary
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Data Maturity

As you become data mature, it’s important to manage your own expectations and be realistic about the value that you’re getting from these investments.
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Data Mining Basics

Data mining basics is an analytical method that uses automation tools like machine learning to extract usable information from massive sets of raw data.
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Data Modeling

What is data modeling and how does it relate to data analysis? This 3-minute read will walk you through the bare essentials.
data organization
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Data Organization

Data organization is the practice of categorizing and classifying data to make it more usable, so it can be easily accessed, processed, and analyzed.
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Data Pipeline

A data pipeline is the structure that facilitates moving data from the applications or systems where it is stored
Data preparation
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Data Preparation (Dataprep)

Data preparation is the process of cleaning, reformatting and modeling your data in order to get it into shape for analytics or other evaluation purposes.
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Data Products

Data needs to be processed to get the most out of it. Data products are what enable users to extract value from this resource.
What is data quality?
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Data Quality

Data quality measures the condition of your data, using different factors. Get in to explore the factors and deep dive into data quality management.
Data Reporting Featured Image
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Data Reporting

Data reporting refers to collecting and formatting raw information and translating it into a digestible format to assess ongoing business performance.
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Data Science Basics

Data science is the multidisciplinary field that focuses on finding actionable information in large, raw or structured data sets to identify patterns.
The Shift to Cloud Analytics
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Data Standardization

Data standardization is the process of converting data to a common format to enable users to process and analyze it.
Data Storytelling
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Data Storytelling

What is data storytellingWhy it’s essentialHow to tell the best storiesData Storytelling Examples What is data storytelling Data storytelling forms...
Python and R visualizations blog featured image
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Data Visualization

A complete guide that will open the door for you to the data visualization world. From basic explanations to advanced design resources and examples
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Data Warehouse Architecture

Data warehouse architecture refers to the design of an organization’s data collection and storage framework, placing it into an easily digestible structure.
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Database Security

Database security uses a wide variety of tools to protect large virtual data storage units, like databases, from external attacks, corruption, and malware.
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Descriptive Analytics

Descriptive analytics gives you a general view of your historic data, to provide a clear, straightforward picture of your company’s operations.
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Deterministic Finite Automata

Deterministic finite automata are finite state machines that accept or reject strings of characters by parsing them through a uniquely determined sequence.
DevOps
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DevOps Continuous Integration

DevOps continuous integration is a development model that focuses on fine tuning and live additions to existing software rather than releasing new versions.
Glossary Diagnostic Analytics Featured Image
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Diagnostic Analytics

Diagnostic analytics describes techniques that let you deep-dive into your data, search for insights, and uncover the reasoning behind certain results.
Edge Analytics
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Edge Analytics

In edge analytics, incoming data streams are analyzed at a non-central point like a sensor or peripheral node, and emphasizes speed and decentralization.
Data Model Development Using Jinja
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Embedded Analytics

embedded analytics refers to the process of plugging a third party’s software into your own app
Sisense Brochure
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Embedded Reporting

Embedded reporting is the method of incorporating BI visualizations, such as dashboards and charts, into software applications for customized viewing.
d3 forced network diagram
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Entity Relationship Diagram

An entities relationship diagram describes how data elements relate to each other, within your business or a certain business process. Read more:
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Financial Data Management

Financial data management is the part of your BI solution that helps monitor information and reporting needs, as well as comply with legal requirements.
Geo Analytics
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Geo Analytics

Geo analytics adds location data to your visualizations, providing a new axis to discover insights for sales, engagement, and marketing departments.
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Google Big Query Data Warehouse

Google BigQuery is a cloud-based and scalable enterprise data warehouse that offers rapid SQL queries and interactive analysis of massive datasets.
The-Data-Behind-the-Healthcare-Industry_Blog_Feature
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Healthcare Analytics Basics

Healthcare analytics basics refers to analyzing current and historic industry data to predict trends, improve outreach, and manage the spread of diseases.
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Healthcare Informatics

Healthcare informatics focuses on gathering and understanding industry data to improve service provision and collaboration between doctors and providers.
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In-Memory BI

In-Memory BI’s claim to fame is to provide an alternative to the hefty data warehouse and OLAP projects. But does it deliver?
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Insights as a Service

Insights as a service use predictive analytics and BI to reveal insights from cloud-based data warehouses and provide solutions to data-specific challenges.
Featured_glossary
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Integrated Analytics

Integrated analytics fuse your data insights into everyday workflows and applications, helping employees and customers make smarter decisions.
Interactive Data Visualizations
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Interactive Analytics

Interactive analytics is an extension of real-time analytics that has the capacity to crunch through huge volumes of unstructured data at scale and speed.
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Interactive Data Visualization

Interactive visualization refers to graphic representations of data, often in the form of dashboards, that improve the way we interact with information.
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KPI Tracking

KPI tracking, the way companies monitor performance metrics, is what your data dashboards are based on. Use it to power your sales and innovations.
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Linux Database

A Linux database is built specifically for the open-source operating system and is generally more stable, safe, and customizable, with reliable uptimes.
Linux Server
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Linux Server

A Linux server is designed to handle the intense demands of larger organizations, and outstrips Windows servers in stability, security, and flexibility.
Location Analytics
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Location Analytics

Location analytics extracts additional insights from transactional data like logistics and supply chains by adding a layer of geolocation information.
Managed Cloud
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Managed Cloud

Managed cloud is a service that helps smaller businesses build servers and infrastructure on the cloud by handling set-up and support on the back-end.
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Marketing Analytics

Marketing analytics is the technology and BI tools marketers use to measure the impact of their strategies and campaigns, with data from various sources.
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Mobile Analytics

Mobile analytics monitor and understand how users interact with an app to gain a better comprehension of their behavior and the application’s performance.
MPP Database
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MPP Database

An MPP database handles operations from multiple processing units simultaneously, providing faster analytics from large datasets and saving server space.
Multi-tenant glossary
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Multi-Tenant

In a multi tenant environment, a single instance of software runs on a server and serves multiple customers by creating a dedicated instance for each one.
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Natural Language Understanding

Natural language understanding helps AI learn how to talk to humans. This technology can be used in features like chatbots and search engine queries.
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OEM Manufacturing

OEM manufacturing refers to providing parts and supplies to companies to incorporate into their own products and resell, saving cost and hassle. .
OEM Partnership
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OEM Partners

OEM partners offer third-party software, including analytics, that you can embed into your product, adding functionality and value for your customers.
OEM Software
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OEM Software

OEM software refers to applications that are sold wholesale to hardware and software manufacturers for the purpose of bundling with existing offerings.
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OLAP, ROLAP, MOLAP, HOLAP

The magic behind OLAP comes from its ability to pre-calculate and pre-aggregate data. But what happens when you need answers NOW?
OLTP Glossary Feature
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OLTP

Online transactional processing is a class of software program that supports transaction-based applications on the internet, like shopping or POS terminals.
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Open Database Connectivity (ODBC)

Open database connectivity (odbc) is an API that allows applications to interact with multiple database systems simultaneously while remaining independent.
Open Source Embedded Analytics
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Open Source Embedded Analytics

Open source embedded analytics are non-proprietary tools that can be integrated with a company’s own software to enable developers to view and modify code.
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Operational Intelligence

Operational intelligence is a data analytics philosophy that focuses on implementing quick business decisions and taking action based on real-time data.
Create financial reports easily
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Operational Reporting

Operational reporting produces detailed reports of day-to-day organizational operations and delivers short-term BI insights that are immediately actionable.
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Predictive Data Analytics

Predictive data analytics uses current and past data to let you make predictions about the future or other unknowns. Learn More!
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Predictive Maintenance

Predictive maintenance is a data-driven process to predict when operational equipment may fail and deploying strategies to avoid downtime and reduce costs.
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Prescriptive Analytics

Prescriptive analytics focuses on finding the best course of action in a scenario, emphasizing actionable insights instead of data monitoring.
product-analytics
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Product Analytics

Product analytics uses AI and machine learning to make sense of customer behavior by providing a unified central view of historical and real-time data.
R-vs-Python-Blog_Featured
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Python for Data Analysis

Python is a multi-purpose programming language popular for its flexibility, as well as its extensive collection of libraries, widely used for analytics.
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Python For Data Science

Python for data science refers to the extensive libraries and tools, including machine learning, that the programming language offers for data analysis.
code-developer-screen
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R Analytics

R analytics is a free, open-source programming language used for data science, statistics, and visualization projects. It's a powerful and versatile tool.
R language
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R for Data Science

R for data science is a popular programming language featuring a catalog of tools including machine learning, along with heavy-duty regression and modeling.
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Real Time Analytics

Real-time analytics gives insights immediately after the data enters the system, allowing businesses to react without delay.
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Real Time Dashboard

A real time dashboard contains visualizations that are automatically updated with current data that can identify emerging trends and evaluate efficiency.
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Redshift Database

Amazon's redshift database is a cloud-based warehouse solution that lets companies store petabytes of data in easy-to-access clusters for analysis and BI.
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Relational Database

Read the definition of a relational database and the benefits of using one to store organizational data.
Retail Analytics
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Retail Analytics

Retail analytics focuses on providing insights related to sales, inventory, customers, and other important aspects crucial for the decision-making process.
self-service bi
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Self-Service Business Intelligence

Self-service bi are data analytics tools that nontechnical users - not just IT and data teams - can use to connect and analyze data and reveal insights
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Self-Service Reporting

Self-service reporting gives users direct access to data analysis, requiring little technical knowledge to get actionable BI insights and accurate reports.
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Snowflake Data Warehouse

The Snowflake data warehouse is a cloud-based tool that supplies companies with flexible and scalable storage while simultaneously hosting solutions for BI.
Stronger SQL: Essential Skills for Data Engineers
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SQL for Data Analysis

SQL for data analysis refers to SQL's ability to perform surprisingly complex data analysis and queries, despite the simplicity of the language.
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Talent Analytics

Talent analytics is a BI tool mainly used by HR departments. It can maximize your team's potential by giving you insights into your employee metrics.
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Text Mining

Text mining involves taking unstructured text (like customer complaints) and organizing it within a database to simplify the process of analyzing it.
Unified Data Management
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Unified Data Management (UDM)

Unified data management (udm) describes the process of consolidating disparate data sources to create a single narrative and build a more agile data model.
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Visual Data Analysis

A visual data analysis will fit data in an interface, like an interactive dashboard, to make it easier for human beings to see patterns and identify trends.
Naive Bayes Sentiment Analysis
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What Is Data Analysis?

Data analysis is the process of manipulating your data for evaluation purposes with the goal of improved business operations and informed decision-making.
Featured_glossary
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What is data lineage?

Data lineage traces the journey of your data. This information is stored as technical metadata and used by database systems to address issues.
White-label-analytics
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White Label Analytics

As an embedded product, white label analytics offer the benefits of data analysis outsourcing without customers having to leave your website or application.
why business analytics
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Why Business Analytics?

Revealing new insights and conclusions from data is the reason why business analytics tools and techniques are necessary for data-driven organizations.
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