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By Raza Ahmed Khan
Data’s value to your organization lies in its quality. Data quality becomes even more important considering how rapidly data volume is increasing. According to conservative estimates, businesses generate 2 hundred thousand terabytes of data every day. How does that affect quality? Well, large volumes of data are only valuable if they’re of good quality, i.e., usable for your organization’s analytics and BI processes.
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By Khurram Haider
If you’re working in the data space today, you must have felt the wave of artificial intelligence (AI) innovation reshaping how we manage and access information. One of the areas affected is data catalogs, which are no longer simple tools for organizing metadata. They’ve evolved dramatically into powerful, intelligent systems capable of understanding data on a much deeper level.
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By Khurram Haider
Information extraction (IE) finds its roots in the early development of natural language processing (NLP) and artificial intelligence (AI), when the focus was still on rule-based systems that relied on hand-crafted linguistic instructions to extract specific information from text. Over time, organizations shifted to techniques like deep learning and recurrent neural networks (RNN) to improve the accuracy of information extraction systems.
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By Khurram Haider
Business leaders find themselves involved in a range of high-priority tasks, most of which require making critical decisions. Let’s say you’re the sales head of a global organization. You’re ready to make an important decision about next quarter’s sales strategy, but you must first look at the right data set. You know it exists somewhere in your organization’s databases, yet it’s not within the arm’s reach.
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By Sunbul Ali
The financial document processing domain has undergone a 360-degree shift in the past decade. It was at the brink of the 1980s when software providers began releasing document management systems aimed at helping companies save time, money, and effort in regard to financial document processing. What started as simple document management systems using Optical Character Recognition to digitize printed financial documents has evolved into advanced, AI-powered solutions.
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By Khurram Haider
What if your document processing system could do more than categorize documents and extract data, no matter the format? That’s exactly what you can do with intelligent document processing (IDP) software. IDP tools adapt to varying structures and formats and understand content to summarize lengthy documents, identify anomalies, and flag errors. The best part? IDP software continuously improves in accuracy the more you use it.
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By Raza Ahmed Khan
The GenAI revolution is well and truly here. To take inspiration from our favorite comfort show, Gilmore Girls, “It’s GenAI’s world, and we’re just living in it.” In fact, McKinsey reports the number of organizations regularly using GenAI has doubled in ten months between their 2023 and 2024 surveys.
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By Raza Ahmed Khan
Your docs are a lot like your family—not in the corporate jargony “we are a family” way, but more in the “can’t live with them, can’t live without them” way. Yes, these docs are crucial in more ways than one, but teams that regularly work with them know that the time they spend searching for, cleansing, and prepping their docs can be better utilized elsewhere.
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By Sunbul Ali
The computer revolution in law took flight in the 1970s with the release of the iconic red “UBIQ” terminal. This innovation completely changed how legal document management was performed. It empowered lawyers to easily browse case law online rather than looking through towering racks of yellowed paper. As the years passed, a wave of new document management solutions emerged.
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By Ammar Ali
Let’s be honest – AI can seem like a bit of a mystery, and with this mystery comes myths and misconceptions. Is it actually that good? Can it handle varying document structures? Can it integrate with my existing systems? Because of this mystery, many companies have yet to take the leap and incorporate AI into their data processes. Today, we’re going to play MythBusters, separate fact from fiction, and show how you can use AI document processing to maximize efficiency and save costs.
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By Astera
With minimal human intervention, you can gain BI insights faster through our automated data warehouse design, development, deployment, and maintenance.
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By Astera
In this video, we will learn how to add tags to a Data Asset in Astera's Data Governance Platform.
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By Astera
Join us in this engaging webinar as we examine the role of AI in automating invoice payments within the retail landscape. We will highlight the significance of data extraction technologies and their ability to enhance payment accuracy and speed. Learn about the challenges faced by retailers and how AI solutions can address these issues effectively.
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By Astera
In this video, we'll guide you through the process of connecting to Microsoft Azure SQL Server using Astera Data Stack. Users can connect to Azure SQL Databases using various objects, including Database Table Source, Database Table Destination, and SQL-related tasks. Contents of the video: Introduction to connecting with Microsoft Azure SQL Server.
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By Astera
In the insurance industry, the claims process plays a vital role in shaping an insurer's reputation, customer satisfaction, and financial performance. However, this process is primarily characterized by the substantial volumes of unstructured data that insurers must adeptly handle and leverage to enhance the customer journey and streamline claims lifecycle management.
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By Astera
The big increase in data, more sources of data, and the need for quick insights mean companies have to move away from slow, fixed methods of handling data. Dynamic ETL emerges as a timely solution, offering the flexibility to process data in real time, adapt to changing formats seamlessly, and scale operations efficiently.
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By Astera
The education sector has always worked with data to guide various processes, most notably student progress. But with powerful, AI-driven data extraction tools impacting other industries, it's time for educators to leverage these tools, accelerate data extraction, and turn data into actionable insights much faster.
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By Astera
A Single Customer View (SCV) is crucial for optimizing marketing ROI from a tech standpoint as it consolidates data from diverse channels, offering a complete customer profile.
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Astera Software is a rapidly-growing provider of enterprise-ready data management solutions. Our goal is to make data-driven insights more accessible than ever through no-code, user-friendly, and automated data extraction, data integration, data warehousing, API management, and EDI solutions.
Features of Astera Centerprise:
- Support for Diverse Systems: Connectivity to a range of structured, unstructured, and semi-structured data sources, including databases, web services, data warehouses, and flat file formats, such as delimited and CSV is the basic staple of all information mapping tools.
- Graphical, Drag-and-Drop, Code-Free User Interface: A code-free environment to create mappings and a graphical, drag-and-drop UI to process data using built-in transformations.
- Ability to Schedule and Automate Jobs: The ability to orchestrate a complete workflow using time and event-triggered job scheduling is a valuable feature in a tool. This automation cuts down the manual work, improving productivity and saving time.
- Instant Preview Feature for Real-Time Testing: Intuitive features like Instant Data Preview help prevent mapping errors at the design time. This functionality lets the user view the processed and raw data at any step of the data process.
- SmartMatch Data Conversion Mapping for Resolving Naming Conflicts: Synonym-driven file reading to resolve discrepancies in field names and business data lineage function to address the challenges of naming conflicts. It can be done by defining synonyms for a word in the synonym dictionary of a particular project.
Empowering Enterprises Across the Globe to Turn Data into Insights at Lightning-fast Speed!