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How to manage data integration during an acquisition

CIO Business Intelligence

Organizations need effective data integration and to embrace a hybrid IT environment that allows them to quickly access and leverage all their data—whether stored on mainframes or in the cloud. How does a company approach data integration and management when in the throes of an M&A?

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Introducing Precisely for Data Integrity

David Menninger's Analyst Perspectives

Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly.


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5 modern challenges in data integration and how CIOs can overcome them

CIO Business Intelligence

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. Heterogeneous sources produce data sets of different formats and structures.

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Security In Automated Document Processing: Ensuring Data Integrity And Confidentiality

Smart Data Collective

A security breach could compromise these data, leading to severe financial and reputational damage. Moreover, compromised data integrity—when the content is tampered with or altered—can lead to erroneous decisions based on inaccurate information. You wouldn’t want to make a business decision on flawed data, would you?

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Start Taking Your Embedded Partnerships Seriously

That means easy embedding, data integrations, seamless automation, total security, and much more. At every step of the way, we offer development teams the tools they need to make their premier analytic applications faster, more efficient, and all with fewer resources than ever before.

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Top 4 Data Integration Tools for Modern Enterprises


Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises.

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Data integrity vs. data quality: Is there a difference?

IBM Big Data Hub

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

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Data & Analytics Maturity Model Workshop Series

Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale

Workshop video modules include: Breaking down data silos. Integrating data from third-party sources. Developing a data-sharing culture. Combining data integration styles. Translating DevOps principles into your data engineering process. Using data models to create a single source of truth.

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Building Best-in-Class Enterprise Analytics

Speaker: Anthony Roach, Director of Product Management at Tableau Software, and Jeremiah Morrow, Partner Solution Marketing Director at Dremio

Tableau works with Strategic Partners like Dremio to build data integrations that bring the two technologies together, creating a seamless and efficient customer experience. Through co-development and Co-Ownership, partners like Dremio ensure their unique capabilities are exposed and can be leveraged from within Tableau.