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Developing an AI Strategy for Your Business: A Comprehensive Guide

Business Analysis Hub

Ensure data quality and governance: AI relies heavily on data. Ensure you have high-quality data and robust data governance practices in place. Analyse data requirements : Assess the data required to build your AI solution. This includes data collection, storage, and analysis.

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EDI Security in Finance and Mortgage: Protecting Sensitive Data in Electronic Exchange

Astera

This holds especially true in the mortgage industry, where highly confidential and personal information is exchanged between multiple parties, including financial institutions, mortgage lenders, borrowers, and government agencies. Ensuring seamless communication and compatibility between different systems can be a significant challenge.

Finance 52
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How to Build a Data Governance Strategy for Your Organization

Astera

An effective data governance strategy is crucial to manage and oversee data effectively, especially as data becomes more critical and technologies evolve. However, creating a solid strategy requires careful planning and execution, involving several key steps and responsibilities.

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What Is Data Governance and Why It Matters?

Astera

Data governance refers to the strategic management of data within an organization. It involves developing and enforcing policies, procedures, and standards to ensure data is consistently available, accurate, secure, and compliant throughout its lifecycle.

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Press Release: Astera Launches Code-Free API Lifecycle Management Solution, Astera Data Services at Big Data LDN 2022

Astera

Astera Data Services enables users to easily secure and manage APIs in one place. Moreover, users can monitor API consumption trends through a live dashboard and convert API metrics into business benefits. Talking about Astera Data Services, Mike A. It really affects the ability to respond to changing data requirements quickly.”

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

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Ethical Concerns With AI/ML – Some Myths vs. Facts

GAVS Technology

A similar school of thought advocates that these technologies should be used in a controlled manner and monitored closely, else they could take over mankind. As bots can work 24/7 and are capable of generating a large amount of data in a very short period, fake news can be generated and made viral in no time.