How Data Quality Impacts Manufacturing 4.0

How Data Quality Impacts Manufacturing 4.0

How Data Quality Impacts Manufacturing 4.0

How Data Quality Impacts Manufacturing 4.0

At a time when major advances in machine learning (ML), artificial intelligence (AI) and internet of things (IoT) are being promoted in the industry, many manufacturers continue to struggle to incorporate advanced analytics into their business processes. Critical to the success of any data analytics initiative is having clean data. The data must be accurately labeled, free of duplicate records, and blended to generate the correct results. This is key to becoming a truly data-driven enterprise.

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Energy Use Case

With EnerHub Powered by Aunsight™️ Golden Record, Upstream Oil & Gas Operator Finally Achieves Total Data Management Solution It Envisioned

Enerhub Case Study

Case Study:

With EnerHub Powered by Aunsight™️ Golden Record, Upstream Oil & Gas Operator Finally Achieves Total Data Management Solution It Envisioned

An oil & gas company faced a huge data problem impacting business operations: inconsistent data in common well attributes across multiple operational systems. To solve this challenge, the company had previously selected a Master Data Management (MDM) tool from a well-known oil and gas software vendor. However, once up and running, the company soon realized that the software complicated and actually worked cross-purpose to its business processes instead of streamlining data.

Less than a year after their original MDM implementation, the oil & gas operator decided to cut its losses and find a solution that aligned with its original vision: an easy-to-use, “super-intuitive” tool with the flexibility to adapt to its culture, workflows, and user needs. The company spent nearly a year evaluating and comparing data management tools and selected EnerHub Powered by Aunsight™ Golden Record.

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Credit Union Uses Daybreak to Deliver Insights Specific to Its Business

Case Study:

Credit Union Uses Daybreak to Deliver Insights

The President of a Michigan credit union wanted to incorporate data analytics for better executive decision-making. As new community banks and credit unions kept moving to his region, he was concerned about the credit union’s ability to compete and distinguish themselves from other local, white glove financial services options. To meet this goal, the president wanted a dashboard to view all member data in one place, but he did not know where to begin.

This case study summarizes how the credit union was able to laser in on what it needed based upon their failed attempts. It needed a solution with a focus on reporting to the end user to deliver insights that would give business outcomes. It needed Daybreak™.

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Provident Bank Case Study

Bank Jumpstarts Journey to Predictive Analytics & AI

Provident Bank, a mid-sized bank with $10 billion in assets, is the oldest community bank in New Jersey with branches across two states. Although they have successfully met their customer’s needs for more than 180 years, they knew that they needed to invest in technologies today that would carry them into the future.

Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.

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Financial Services

Bank Jumpstarts Journey to Predictive Analytics & AI

Bank Jumpstarts Journey to Predictive Analytics & AI

Provident Bank, a mid-sized bank with $10 billion in assets, is the oldest community bank in New Jersey with branches across two states. Although they have successfully met their customer’s needs for more than 180 years, they knew that they needed to invest in technologies today that would carry them into the future.

Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.

Get Started