Big Data Analysis Development Business Intelligence Software – “In addition to delivering deep insights based on business data, [Analytics] allows users to search for trends using natural language.”
Big Data Analysis Development Business Intelligence Software
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Business Intelligence Big Data
This paper examines how big data analytics services improve Big Data Analysis Development business intelligence. This paper proposes an ontology of big data analytics, presents a big data analytics service-oriented architecture (BASOA), and applies BASOA to Big Data Analysis Development business intelligence. Our surveyed data analysis shows that BASOA can improve BI and enterprise information systems.
This paper examines BI intelligence’s temporality, expectability, and relativity. Customers and decision makers expect these traits from BI in systems, products, and services of organizations. This paper’s approach may help develop business analytics, big data analytics, BI, big data science, and big data computing.
1. Big data reigns
Big data has transformed innovation, research, development, management, and Big Data Analysis Development business [2, 3, 4]. Big data analytics services have expanded markets. According to IDC (International Data Corporation), big data and analytics-related services marketing in Asia/Pacific (Excluding Japan) will grow from US$3.8 billion in 2016 to US$7.0 billion in 2019 at a 16.3% CAGR .
Big data and its emerging technologies, including big data analytics, are revolutionizing business and creating new opportunities for academia and enterprises [6, 7, 4, 1]. Big data analytics has become a mainstream market across industries, organizations, geographic regions, and individuals to facilitate big data.
2. Big Data Ontology Analytics
This section proposes a big data analytics ontology and examines its relationship to data analytics. This section starts with big data analytics basics. Big data analytics involves collecting, organizing, and analyzing big data to find, visualize, and display patterns, knowledge, intelligence, and other information [14, 7]. Big data analytics analyzes, acquires, and visualizes knowledge and intelligence from big data .
Big data analytics uses cutting-edge ICT, mathematics, OR, ML, and decision sciences for big data [6, 2]. Big data analytics comprises descriptive, predictive, and prescriptive analytics [16, 7]. Big data analytics, therefore,
- Big data descriptive analytics is descriptive analytics for big data [17, 18, 7], used to discover new, nontrivial information [18, p. 2] and explain the characteristics of entities and relationships among entities in big data [19, p. 611]. It addresses issues like what happened, when, and what is happening. Big data descriptive analytics includes pay-per-click and email marketing web analytics .
- Big data predicative analytics forecasts trends by answering questions like what will happen, what will likely happen, and why it will happen [17, 21, 4]. Based on big data, predicative analytics models future events [19, p. 611]. Big data predicative analytics can predict terrorist targets.
- Big data prescriptive analytics solves problems like what to do, why to do it, and how to get the best result under uncertainty [16, p. 5]. Big data prescriptive analytics can optimize an e-commerce company’s marketing strategy.
Building An Open Data Cloud Ecosystem
Connect to a wide range of sources such as file and wire, popular Big Data Analysis Development business applications, cloud and on-premise databases, custom applications and more, with our easy-to-use connectors.
Use enhanced self-service data preparation and management modules to clean, transform, enrich, and catalog the data you want to analyze.
Hold conversations with our smart AI assistant, generate automatic insights with one click, predict future trends, perform cognitive and what-if analysis, configure smart alerts and more.
Build interactive and interactive reports and dashboards with our easy drag-and-drop interface. Use a wide variety of charts, widgets, pivot tables and tabular view components to visualize your data.
Benefits Of Data Analytics
Big Data Analysis Development Businesses and organizations have questions and goals. To answer these questions and track performance against these goals, they gather the necessary data, analyze it, and determine what actions are taken to achieve the goals.
On the technical side, raw data is collected from Big Data Analysis Development business systems. Data is processed and then stored in data warehouses, the cloud, applications, and files. Once it is stored, users can access the data, starting the analysis process to answer business questions.
BI platforms also offer data visualization tools, which convert data into charts or graphs and present it to any key stakeholder or decision maker.