How AI and Automation are Revolutionizing Data Abstraction in 2023?

 

Data plays a pivotal role in today's corporate landscape, providing essential information for analysis and decision-making. However, the rapid growth of technology and data collection has led to a massive influx of information, including irrelevant and redundant details, making data abstraction a critical process to extract meaningful insights.  Unstructured data, accounting for a significant portion of business data, presents a challenge, with 52% of data classified as "dark" or of unknown value and only 15% considered business important. Data abstraction is the solution aimed at removing unnecessary data and delivering a simplified representation of the whole, enhancing data usability.  Three Levels of Data Abstraction  Data abstraction is a process of hiding the details of data representation from the user. This allows users to work with data without having to know how it is physically stored. There are three levels of data abstraction:  Physical level: This is the lowest level of abstraction. It describes how the data is actually stored in the database. This level is concerned with the physical details of data storage, such as the file format, the location of the data on disk, and the way the data is indexed.  Logical level: This is the middle level of abstraction. It describes the data in terms of its logical structure. This level is concerned with the relationships between different data entities, such as tables, columns, and rows.  View level: This is the highest level of abstraction. It describes the data in terms of how it is presented to the user. This level is concerned with the way the data is displayed, such as the format of the data, the order of the data, and the filters that are applied to the data.  The three levels of data abstraction are related to each other. The physical level is the foundation on which the logical level is built. The logical level is the foundation on which the view level is built.  Benefits of data abstraction  In the past, data abstraction was a manual process that was time-consuming and error prone. However, with the advent of artificial intelligence (AI), it is now possible to automate the process of data abstraction. This has led to a number of benefits, including:  Increased accuracy: AI-powered data abstraction algorithms are able to identify and remove irrelevant data with greater accuracy than humans.  Reduced time to market: AI-powered data abstraction can be used to automate the entire process of data abstraction, from identifying the necessary data entities to finding relations among the entities. This can significantly reduce the time it takes to get data into production.  Improved scalability: AI-powered data abstraction algorithms can be scaled to handle large datasets. This makes it possible to use data abstraction to improve the efficiency and accuracy of data analysis for even the largest organizations.  As a result of these benefits, AI-powered data abstraction is becoming increasingly popular. In fact, a recent study by Gartner found that 70% of organizations will be using AI-powered data abstraction by 2023.  How AI Can Change Data Abstraction Process Flow?  AI-powered data abstraction services have emerged, leveraging machine learning and AI algorithms to streamline the process, reduce human intervention, and enhance efficiency. AI plays a major role in transforming data abstraction in the following ways:  Identifying Necessary Data Entities: AI facilitates accurate identification of essential data entities while efficiently removing irrelevant data. Its integration improves corporate efficiency by up to 40% and ensures that the right data is retained for analysis.  Identifying Key Properties of Entities: With AI's capabilities, data properties and attributes can be accurately identified, eliminating human errors and enhancing data filtration accuracy.  Connecting Data Entities: AI algorithms excel in identifying patterns and relationships among data entities, making the process of connecting data patterns seamless and reliable.  Mapping Properties to Entities: AI speeds up and improves the accuracy of property mapping by leveraging machine learning algorithms to infer data mapping predictions.  Removing Duplicate Data Entities: AI effectively identifies and removes duplicate data, preventing data decay and reducing data quality issues.  Validating Data Outcomes: AI's integration in the data validation process ensures that the data abstracted aligns with the desired data, leading to accurate and high-quality databases.    Data abstraction is a multi-layered process involving the physical level (data storage), the logical level (data organization), and the view level (data presentation to users). AI revolutionizes each of these layers, offering efficiency, accuracy, and scalability.  Conclusion    AI and automation have transformed data abstraction in 2023, providing businesses with the ability to harness data effectively, make informed decisions, and stay ahead in a data-driven world. By leveraging AI-powered data abstraction services, businesses can optimize their processes and focus on core activities, ensuring data integrity and future success. For reliable and professional AI-driven data abstraction services, companies like Outsource BigData stand as trusted partners in this evolving landscape. Visit their official website to learn more and explore the benefits of AI-augmented data abstraction services.    To Read More Visit: https://outsourcebigdata.com/blog/data-abstraction-services/how-ai-automation-can-change-data-abstraction-process-flow-in-2022-2/

About AIMLEAP 

Outsource Bigdata is a division of Aimleap. AIMLEAP is an ISO 9001:2015 and ISO/IEC 27001:2013 certified global technology consulting and service provider offering AI-augmented Data Solutions, Data Engineering, Automation, IT Services, and Digital Marketing Services. AIMLEAP has been recognized as a ‘Great Place to Work®’.  

  

With a special focus on AI and automation, we built quite a few AI & ML solutions, AI-driven web scraping solutions, AI-data Labeling, AI-Data-Hub, and Self-serving BI solutions. We started in 2012 and successfully delivered projects in IT & digital transformation, automation-driven data solutions, on-demand data, and digital marketing for more than 750 fast-growing companies in the USA, Europe, New Zealand, Australia, Canada; and more.  

 

 

An ISO 9001:2015 and ISO/IEC 27001:2013 certified  

 

Served 750+ customers  

 

11+ Years of industry experience  

 

98% client retention  

 

Great Place to Work® certified  

 

Global delivery centers in the USA, Canada, India & Australia  

 

  

Our Data Solutions 

 

  

APISCRAPY: AI driven web scraping & workflow automation platform 

APYSCRAPY is an AI driven web scraping and automation platform that converts any web data into ready-to-use data. The platform is capable to extract data from websites, process data, automate workflows, classify data and integrate ready to consume data into database or deliver data in any desired format.  

 

  

AI-Labeler: AI augmented annotation & labeling solution 

AI-Labeler is an AI augmented data annotation platform that combines the power of artificial intelligence with in-person involvement to label, annotate and classify data, and allowing faster development of robust and accurate models. 

 

  

AI-Data-Hub: On-demand data for building AI products & services 

On-demand AI data hub for curated data, pre-annotated data, pre-classified data, and allowing enterprises to obtain easily and efficiently, and exploit high-quality data for training and developing AI models. 

 

 

PRICESCRAPY: AI enabled real-time pricing solution 

An AI and automation driven price solution that provides real time price monitoring, pricing analytics, and dynamic pricing for companies across the world.  

 

  

APIKART: AI driven data API solution hub  

APIKART is a data API hub that allows businesses and developers to access and integrate large volume of data from various sources through APIs. It is a data solution hub for accessing data through APIs, allowing companies to leverage data, and integrate APIs into their systems and applications.  

 

 

Locations: 

USA: 1-30235 14656  

 

Canada: +1 4378 370 063  

 

India: +91 810 527 1615  

 

Australia: +61 402 576 615 

 

  

Email: Sales@aimleap.com