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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

5) How Do You Measure Data Quality? Oftentimes, the data being collected and used is incomplete or damaged, leading to many other issues that can considerably harm the company. There are a lot of strategies that you can use to improve the quality of your information. Table of Contents. 1) What Is Data Quality Management?

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4 Data-Driven Ways to Improve Employee Engagement

datapine

Start by monitoring your current levels of employee training and engagement. Send it out every six months, along with frequent pulse surveys that check in on your employees regarding specific matters (such as work-life balance or company culture). Engaged employees understand their purpose and impact on the organization.

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12 Rules for Data Storytelling

Juice Analytics

Are you ready to learn how to be a data storyteller, but don’t have enough time to review the many great resources ? A data story will express your point of view Data can’t tell a story without your help. Don’t hide data that would counter your view. Don’t hide your agenda and message. No problem.

Metrics 138
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Top 10 Management Reporting Best Practices To Create Effective Reports

datapine

In this blog post, we’re going to give a bit of background and context about management reports, and then we’re going to outline 10 essential best practices you can use to make sure your reports are effective. We’ll also examine for some of the examples that illustrate these best practices in action created with a modern report tool.

Reporting 263
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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging. Let’s look at an example use case.

Data Lake 111
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Build an end-to-end serverless streaming pipeline with Apache Kafka on Amazon MSK using Python

AWS Big Data

However, it can be challenging to set up a Kafka cluster along with other data processing components that scale automatically depending on your application’s needs. You risk under-provisioning for peak traffic, which can lead to downtime, or over-provisioning for base load, leading to wastage.

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5 signs your agile practices will lead to digital disaster

CIO Business Intelligence

But speaking to many IT leaders, there are often gaps between how IT runs Scrum, Kanban, or other agile practices and what CIOs need in order to achieve digital transformation objectives. We discussed how many agile teams focus on rituals without truly understanding the manifesto’s objectives or the organization’s goals.