Name: Digital Hive
Author: Digital Hive

Communications Outsourcing

Help Desk

Web and Video Conferencing

Customer Support

Batch Management Software

Kubernetes Monitoring

Development

Business Intelligence (BI)

Collaboration

Enterprise Feedback Management

Org Chart

Payment Facilitation

Privacy Policy Generators

Project Portfolio Management

Enterprise

Accounting

Online Trading

Finance and Accounting

Applicant Tracking

Corporate Learning Management

Credentialing

Employee Performance Management

HR Compliance

HR Management

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AI Governance

Cloud Storage

Container Management

Endpoint Encryption

File Sync and Share

Fraud Detection

HTML Editors

High Availability Cluster

IT Asset Management

Incident Response

Integration Platform as a Service (iPaaS)

Network Operating Systems

Network Performance Monitoring

Phishing Detection and Response

Remote Monitoring and Management

Software Defined Storage (SDS)

System Monitoring

Traffic Switching

Unified Endpoint Management (UEM)

User Virtualization

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Content Management

Email Marketing

Graphics

Headless CMS

Market Intelligence

Marketing Automation

Online Reputation Management

Social Media Management

Social Media Publishing

Survey & Forms Building

Web Analytics

Marketing

Project Management

Writing and Proofreading Tools

Professional Services

Customer Relationship Management (CRM)

Social Commerce

Sales

Intrusion Detection

Secure Access Service Edge (SASE)

Security

Auto Repair

Building Information Modeling (BIM)

Emergency Notification

HIPAA Compliance

Homeowner's Association (HOA) Management

Insurance Agency Management

Intelligent Document Processing

Investment Portfolio Management

Retail Analytics

Vertical-Specific

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Digital Hive is an analytics catalog platform that aims to consolidate insights from multiple platforms into a single, user-friendly portal. It serves as a centralized location for all analytics content, facilitating easy access to the required information. Digital Hive is designed for companies of various sizes, catering to professionals in industries such as business analysis, data analysis, data science, IT, marketing, finance, healthcare, retail, manufacturing, and financial services.

**Unified Analytics Portal**: Digital Hive consolidates insights from multiple platforms into a user-friendly portal, allowing users to access all analytics content in one place.

**Customizable Self-Service Portal**: The platform offers a customizable and self-service portal, enabling users to personalize their analytics experience by creating tailored 'Hives' for internal and external users.

**Real-Time, On-Demand Insights**: Users can obtain real-time, on-demand views of their business within minutes, eliminating the need for static spreadsheets and screenshots.

**Analytics Catalog and Discovery**: Digital Hive provides a user-friendly interface that surfaces all available analytics, utilizing metadata, comments, and ratings to guide users to trusted and certified insights.

**Interactive Data Storytelling**: Users can create real-time interactive data stories by selecting assets from different platforms and adding narrative to facilitate understanding and decision-making.

**Focus on Analytics Adoption and Governance**: Digital Hive simplifies underlying platforms, allowing users to focus on utilizing analytics effectively. It also supports analytics governance through publishing, categorizing, and certifying key reports and dashboards.

**Search, Tag, and Enrich Metadata**: The self-service analytics catalog enables users to search, tag, and rate report metadata, facilitating content organization and discovery.

**Unified Dashboards**: Digital Hive allows users to create and share real-time unified views of all their analytics by dragging and dropping assets from different platforms onto a single page.

**Storyboards for Enhanced Understanding**: Users can enhance data understanding and decision-making by adding commentary, images, PDF documents, and other contextual information to their data storyboards.

**Branded and Personalized Experiences**: Digital Hive enables users to fully brand and customize their enterprise portal, tailoring the experience to individual roles and preferences.

Microsoft BI is a business intelligence product used for data analysis and generating reports on server-based data. It features unlimited data analysis capacity with its reporting engine, SQL Server Reporting Services alongside ETL, master data management, and data cleansing.

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Digital Hive

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BI Platform

Administration via Windows App

Administration via MacOS App

Administration via Web Interface

Live Connection to External Data

Snapshot of External Data

In-memory data model

OLAP (Pre-processed cube representation)

ROLAP (SQL-layer querying)

Multi-Data Source Reporting (Blending)

Data warehouse / dictionary layer

ETL Capability

ETL Scheduler

Supported Data Sources

Data sources that can be consumed by the application.

MS Excel Workbooks

Text Files (CSV, etc)

Oracle

MS SQL Server

IBM DB2

Postgres

MySQL

ODBC

Cloudera Hadoop

Hortonworks Hadoop

EMC Greenplum

IBM Netezza

HP Vertica

ParAccel

SAP Hana

Teradata

Sage 500

Google Analytics

BI Standard Reporting

Standard reporting means pre-built or canned reports available to users without having to create them.

Pixel Perfect reports

Pixel Perfect reports are highly-formatted reports with graphics and ability to preview the report before printing.

Customizable dashboards

Customizable dashboards are dashboards providing the builder some degree of control over the look and feel and display options.

Report Formatting Templates

Ad-hoc Reporting

Ad-Hoc Reports are reports built by the user to meet highly specific requirements.

Drill-down analysis

Drill down analysis is the ability to get to a further level of detail by going deeper into the hierarchy.

Formatting capabilities

Ability to format output e.g. conditional formatting, lines, headers, footers.

Predictive modeling

Predictive modeling is the ability to build future forecasting models.

Integration with R or other statistical packages

Integration with the open-source R predictive modeling environment.

Report sharing and collaboration

Report sharing and collaboration is the ability to easily share reports with others.

Report Output and Scheduling

Ability to schedule and manager report output.

Publish to Web

Publish to PDF

Output Raw Supporting Data

Report Versioning

Report versioning is the assignment of version numbers to each version of a report to help in tracking.

Report Delivery Scheduling

Report Delivery Schedule is the ability to have reports delivered to a destination at a specific data and time.

Delivery to Remote Servers

Ability to deliver reports to remote servers

Data Discovery and Visualization

Data Discovery and Visualization is the analysis of multiple data sources in a search for patterns and outliers and the ability to represent the data visually.

Pre-built visualization formats (heatmaps, scatter plots etc.)

Pre-built visualization formats are canned visualization types that can be selected to visualize different kinds of data.

Location Analytics / Geographic Visualization

Location analytics is the visualization of geographical or spatial data.

Predictive Analytics

Predictive Analytics is the ability to build forecasting models based on existing data sets.

Support for Machine Learning models

Machine learning refers to computer programs that can learn when exposed to new data.

Pattern Recognition and Data Mining

Pattern recognition and data mining mean the ability to recognize hidden patterns in large quantities of data.

Access Control and Security

Access control means being able to determine who has access to which data.

Multi-User Support (named login)

Named model access means that users have access based on name and password.

Role-Based Security Model

Role-based access means that access to data is determined by job or position in the corporation.

Multiple Access Permission Levels (Create, Read, Delete)

Multiple access permission levels means that different levels of users have different rights.

Report-Level Access Control

Report-level access control means that the type of report determines who has access to it.

Table-Level Access Control (BI-layer)

Field-Level Access Control (BI-layer)

Single Sign-On (SSO)

Allows users to use one set of login credentials to access multiple applications

Digital Hive

Overview

What is Digital Hive?