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Testing New AI Applications is Crucial Before Bringing them to Market

Smart Data Collective

Modern methods of software development take a more systematic approach to testing, in accordance with the IBM Rational Unified Process (RUP). It is very important to identify errors in the early stages of development, since later the elimination of such errors can entail significant costs or even require starting from scratch.

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Big Data Sets Impressive New Standards On Integrated Business Systems

Smart Data Collective

Author James Kobielus, the lead AI and data analyst for Wikibon and former IBM expert, said that there are a number of ways that integrated business systems are tapping the potential of AI and big data. You will likely find that integrated software solutions are significantly more cost-efficient in comparison to several stand-alone systems.

Big Data 192
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Replacing Legacy. Part 5: Cloud, SaaS Legacy, and AI

Analysts Corner

There might be various reasons behind such a move, such as increased costs, imposed new regulations, not following SLA (Service Level Agreement), or a failed reputation. And IBM seems to be a leader in leveraging AI to modernize legacy systems. Alternatively, IBM conducts COBOL-to-Java translation with their code assistant.

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Interesting statistics around big data, data analysis, and usage

Analysts Corner

Data Analysis (Image created using photo and elements in Canva) Evolution of data and big data Until the advent of computers, limited facts were collected and documented, given the cost and scarcity of resources and effort to capture, store, and maintain them. Food for thought and the way ahead!

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Leveraging AI and Workflow Automation in Manufacturing

Argon Digital

By integrating AI and automation into various processes, manufacturers can unlock a myriad of benefits, leading to increased efficiency, reduced costs, and enhanced overall productivity. Inventory Management : AI-powered demand forecasting can help manufacturers maintain optimal inventory levels, reducing storage costs and avoiding stockouts.

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Should You Have Separate Document, Time-Series, NoSQL and SQL Databases or Can a Single Database Support All of These Data Types and Requirements?

Actian

Primarily, Relational DataBase Management Systems (RDBMS) managed the needs of these systems and eventually evolved into data warehouses, storing and administering Online Analytical Processing (OLAP) for historical data analysis from various companies, such as Teradata, IBM, SAP, and Oracle.

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The Role of Artificial Intelligence in Business Process Automation: A Comprehensive Analysis

CMW Lab Blog

Predictive Analytics Business Impact: Area Traditional Analysis AI Prediction Benefit Forecast Accuracy 70% 92% +22% Risk Assessment Days Minutes 99% faster Cost Prediction ±20% ±5% 75% more accurate Source: McKinsey Global Institute Implementation Strategies 1.