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Latest Big Data Whitepapers


The Modern Analytics Checklist

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.


Enterprise Architect’s Guide

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.


Data Warehouse Automation

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.


Real-Time Data Pipeline Automation

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.


Speed innovation and increase agility with end-to-end automation
By automating every phase of your software delivery lifecycle—build, test, and run—you can deliver the efficiency, agility, and quality your business needs now. Download our e-book to learn about: Eliminating gaps and blind spots between Dev and Ops teams Integrating and orchestrating data flows from disparate sources Auto-scaling resources for optimal reliability, quality, and cost... Read More

Deliver scalable and reliable data and analytics projects with workflow orchestration
Data and analytics projects play a vital role in digital transformation. This white paper explores the essential role of workflow orchestration across the data lifecycle, from ingestion and integration to workflow creation. Learn how you can: Orchestrate disparate data sources across diverse infrastructure Maintain consistency and quality at enterprise scale Deliver insights to users automatically,... Read More

Increase Your Data Lake ROI

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.


HPCaaS vs on-Premise vs public cloud: A comparative outlook

One of the obstacles for large on-premise clusters are the requirements for high-end data centers in addition to the challenge of ever-increasing energy costs. Large cloud providers have increased their focus on HPC and added more specialized HPC services to their offerings. They leverage the success of their cloud computing ecosystem and are perceived by some to have the most agile and flexible solution available; allowing you to pay on a per-use basis and to adjust your capacity on the fly to meet your needs. But is this really a cost effective long-term strategy for running AI workloads or simulations that can benefit from capacity at scale?


Unlocking analytics insights

Many analytics and business intelligence tools today reduce analytics to a visualisation exercise. Today’s challenges require more than self-service applications that only produce descriptive visualizations based on limited data. Yet when self-service tools focus on data visualisation, they minimize the importance of data governance and data integrity in enterprise settings. This limits our ability to gain true insights from our data and make meaningful business decisions.


Improving data governance for increased profitability

The connection between better data governance and increased revenue is not often made, but in this white paper Erwin lays out why everyone from executives and down should take ownership of it. Having a better understanding of data and the different types of risks involved in different types of data means businesses can move beyond… Read More



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