Remove Data Integration Remove Data Processing Remove Data Quality Remove Forecasting
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NLP Isn’t Enough. Leading Financial Services Companies Are Now Moving to Conversational AI.

CIO Business Intelligence

Juniper Research forecasts that in 2023 the global operational cost savings from chatbots in banking will reach $7.3 As with all financial services technologies, protecting customer data is extremely important. Data integration can also be challenging and should be planned for early in the project. .

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. QuickSight offers scalable, serverless visualization capabilities.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Unlike traditional databases, processing large data volumes can be quite challenging. How to Choose the Right Big Data Analytics Tools?

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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Systematize governance. Create core feedback mechanisms.

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Unified Data Clears the Roadblocks of Your Hybrid Cloud Journey

Jet Global

This approach helps mitigate risks associated with data security and compliance, while still harnessing the benefits of cloud scalability and innovation. Simplify Data Integration: Angles for Oracle offers data transformation and cleansing features that allow finance teams to clean, standardize, and format data as needed.

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What is Data Mapping?

Jet Global

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. The first step of data mapping is defining the scope of your data mapping project.

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Are You in Control of Your JDE or EBS Data?

Jet Global

If your finance team is using JD Edwards (JDE) and Oracle E-Business Suite (EBS), it’s like they rely on well-maintained and accurate master data to drive meaningful insights through reporting. For these teams, data quality is critical. Ensuring that data is integrated seamlessly for reporting purposes can be a daunting task.