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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

While different companies, regardless of their size, have different operational processes, they share a common need for actionable insight to drive success in their business. Advancement in big data technology has made the world of business even more competitive. This eliminates guesswork when coming up with business strategies.

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How can CIOs safely unleash generative AI on their company’s data?

CIO Business Intelligence

However, many business leaders hesitate to adopt it due to security fears. IBM reports that 96% of executives see adopting generative AI as increasing their organisation’s chances of experiencing a security breach within the next three years. How can business leaders balance these two conflicting considerations?

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool like Amazon QuickSight may be more effective for your business. These visualizations and reports can be securely shared with teams across the organization.

Metrics 104
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. 4 – Data Reporting.

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Foote Partners: bonus disparities reveal tech skills most in demand in Q3

CIO Business Intelligence

There were also a host of other non-certified technical skills attracting pay premiums of 17% or more, way above those offered for certifications, and many of them centered on management, methodologies and processes or broad technology categories rather than on particular tools.

Testing 83
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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data. Data can be organized into three different zones, as shown in the following figure.

Data Lake 102
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Build and share a business capability model with Amazon QuickSight

AWS Big Data

LOB Category Capability Recruitment Manage Applicant Experience Manage Application Activities Process Application Follow-Ups Pursue Automated Leads Sale Service Engage Customer Provide Needs Assessment Tools Provide Service Information After the map is defined and captured, each business capability can be mapped to APIs that are implemented for it.