Remove Data Modelling Remove Documentation Remove Reference
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5 Types of Requirements Documents Business Analysts Create

Bridging the Gap

Imagine you are ready to dive deep into a new project, but amidst the sea of information and tasks, you find yourself at a crossroads: What documents should you create to capture those crucial requirements? The path to success lies in understanding the power of documentation. It defines the scope of the project.

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Chat GPT as a tool for business analysis

Analysts Corner

It is widely used as a reference and training tool for business analysts. AI : The BABOK Guide defines various tasks and concepts related to business analysis, including requirements elicitation and analysis, process and data modeling, and stakeholder communication and management. Some suggestions include: 1.

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Tackling Bias in AI Translation: A Data Perspective

Smart Data Collective

Understanding Bias in AI Translation Bias in AI translation refers to the distortion or favoritism present in the output results of machine translation systems. This bias can emerge due to multiple factors, such as the training data, algorithmic design, and human influence.

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Leveraging Unstructured Financial Data with AI Document Processing

Astera

AI-based document processing is transforming the finance industry by unlocking the potential of unstructured data and improving data analysis, compliance, risk management, and decision-making. This technology can analyze vast amounts of data in real time, enabling financial institutions to make timely decisions.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data. OCR is widely used to digitize all kinds of physical documentation.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data. OCR is widely used to digitize all kinds of physical documentation. REFERENCES. [1] Predictive Analytics.

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Replacing Legacy. Part 3: Conversion & Data Mapping

Analysts Corner

That results in the conversion layer requiring data mapping as a BA artifact. Let’s talk about mappings We already discussed the massive challenge of reinventing the legacy Data Models, so let’s assume you have already done it. They should be documented and considered by test and automation tests.