Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights which analysts and business users can translate into tangible business value.

• ·       Capture: Data acquisition, data entry, signal reception, data extraction
• ·       Maintain: Data warehousing, data cleansing, data staging, data processing, data architecture
• ·       Process: Data mining, clustering/classification, data modelling, data summarization
• ·       Communicate: Data reporting, data visualization, business intelligence, decision making
• ·       Analyze: Exploratory/confirmatory, predictive analysis, regression, text mining, qualitative analysis 

Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial such as when two similar companies need to merge their databases and scientific combining research results from different bioinformatics repositories, for example domains. Data integration appears with increasing frequency as the volume that is, big data and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users. The data being integrated must be received from a heterogeneous database system and transformed to a single coherent data store that provides synchronous data across a network of files for clients.

MARKET ANALYSIS

Data science platform incorporates a group of latest generation technologies and design that square measure specially designed as a framework of the whole information science project. It consists of tools that square measure needed to execute the life cycle of the info science project, that consists of various phases like information thought, integration & exploration; model development, and model readying. Within the present state of affairs, it has become a essential investment alternative that has considerably contributed to the expansion of the good and digital trade.

The report doesn't take into account open supply platforms like R and Python and it solely evaluates industrial information science platform vendors. What is more, the market is assessed supported sort into solutions and services. The market is additionally classified supported user into banking, money services, and insurance (BFSI); telecommunication; transportation & logistics; healthcare; producing, and others. The market is analysed supported four regions North America, Europe, Asia-Pacific, and Lamea.

Adoption of the info science platform in rising markets, as well as Brazil, the Gulf Cooperation Council (GCC) countries, and African countries is at a aborning stage, not like that in developed markets like North America and Europe. However, the potential impact of increased analytic solutions and services on business activities has exaggerated within the region. What is more, the relative importance of assortment {information of knowledge} in most of the native economies and also thought to extract unjust insights from the info square measure anticipated to fuel the demand for data science platform services and solutions.

This report includes a study of the info science platform market with regard to growth prospects and restraints supported the regional analysis. The study includes Porters five forces analysis of the trade to see the impact of suppliers, competitors, new entrants, substitutes, and patrons on the market growth.

The data science platform system contains solutions and repair suppliers like Microsoft Corporation, International Business Machines Corporation, SAS Institute, Inc., SAP SE, Rapid Miner, Inc., Dataiku SAS, Apteryx, Inc., honest Isaac Corporation, Math Works, Inc, and Teradata, Inc.

Abstract Submission link : https://datascience.conferenceseries.com/abstract-submission.php.