Logistics industry has to deal with data from multiple sources including bills of lading, customs declaration forms, proofs of delivery, and others. Then they have to ensure the data is prepped, extracted, parsed, converted to the right format and then analyzed. Given how important logistics is in today’s market, it is no wonder that McKinsey Global Supply Chain Leader Survey 2024 reported 74% of respondents were interested in advanced digital and AI-based tools for planning and scheduling.
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By Raza Ahmed Khan
Accounts payable (AP) automation is on the rise as finance teams are realizing the benefits of AP automation solutions currently on the market. Teams that achieve partial automation in their AP processes are seeing considerable benefits in terms of time, cost, and efficiency. With vendors now integrating AI technologies into their software solutions, the potential AP automation benefits promise to change the face of accounts payable altogether.
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By Raza Ahmed Khan
Businesses across various sectors want to leverage AI to increase efficiency, reduce cost, enhance customer experience, or do all that in one go. The mortgage industry is feeling it, too, thanks to the several potential areas where AI technologies can impact. For instance, AI can help mortgage lenders by: In fact, according to a Fannie Mae survey, mortgage lenders believe compliance, underwriting, and property valuation are all ripe for AI integration.
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By Khurram Haider
Documentation forms an integral part of operations in almost every industry. Take logistics and transportation, for example, where companies process hundreds of thousands of documents daily to keep the goods in motion and the supply chain functional. So, what are logistics companies doing to handle such a vast number of documents? More importantly, how can they use the intelligent document processing (IDP) technology to manage their documents and extract the data they need?
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By Usman Hasan Khan
Over the last decade, data has been hailed as the new oil, the new gold, the new currency, the new soil, and even the new oxygen. All these comparisons drive home the same point: data is important. If you’re running a business today, you need data for informed decision-making and strategy development. However, reliably extracting this data is a constant responsibility.
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By Usman Hasan Khan
Bank statements contain useful financial information that can be turned into important insights. With the era of manual bank statement extraction firmly in the past, intelligent document processing (IDP) and artificial intelligence (AI) offer a better way of processing bank statements and obtaining the valuable data they contain.
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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 Astera
Handling large volumes of diverse data from multiple sources typically involves consolidation, reconciliation, and integration into new formats. It may seem like this process would demand more time and IT resources. But with Astera, you can automatically ingest data from multiple sources, automatically parse and map it, and deliver it to your preferred destination, without relying on any IT support.
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By Astera
In this webinar, our experts- Jay Mishra and Abdullah Rafiq, demonstrate how Astera Intelligence can streamline data extraction, improve accuracy, and eliminate manual intervention. Explore how we can help you.
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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 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
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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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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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!