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The Path to Artificial Intelligence in Healthcare

There is a lot of excitement about Artificial Intelligence. The excitement is certainly warranted based on the potential that these solutions can offer. In an industry that has massive amounts of data and is very dependent on the data to both run efficiently and, more importantly, delivery high quality patient care any technology which can […]

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Information Governance – Essential Ingredient for Business Value

In my last blog, you may recall that we were discussing the value and the need for Standards and Templates for ensuring a consistent and efficient use of the Data Lake, both in its population (supplying) and in its retrieval (consuming) of information. To achieve this level of consistency and efficiency, as well as reliability, […]

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Working with the Data Lake Aggregator – Standards and Templates

In my previous blog, I described the concept of an “Information Catalog” and how it plays a vital role in ensuring communication between the Data Lake Aggregator and Suppliers and Consumers is efficient and effective due to the common language that it provides. I also included the following diagram as an example of how the […]

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Data Lake as Aggregator – The Critical Role of the Catalog

My previous blog talked about a Data Lake using a Supplier-Aggregator-Consumer analogy and talking about the roles each of these parties play. One factor that is critical to the success of this approach is the use of a common vocabulary that ensures efficiency and effectiveness in the interactions and collaborations between the parties. The implication […]

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Data Lake Participants – Roles and Responsibilities

As you may recall, in my last blog I introduced the analogy of the Aggregator to describe utilizing a Data Lake as a Consolidator of information, and I mentioned the three key roles in this model: the Supplier, the Aggregator and the Consumer. In this post I will provide a little more detail on the […]

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Common Ingestion Framework

Big Data is the way to move forward for all enterprises today. May it be healthcare, retail, finance or manufacturing, everyone is at different stages in their journey to create their industry-grade, enterprise-ready Data Lake repository. Data Lake forms the core foundation for companies in their journey to build state-of-the-art intelligent applications and provide cutting-edge […]

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Data Lake Consolidation – the Aggregator Analogy

In my last blog, I introduced the concept of the Data Lake as a Consolidator and the critical success factor of applying robust Information Governance to this environment. In this post, I want to introduce an analogy to help visualize this environment and the parties involved. So, a Data Lake as Consolidator. What does that […]

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Data Lakes and the Information Governance Critical Success Factor

Since my last post I’ve been working for a client that is actively engaged in establishing a Data Lake for the purpose of supporting their analytics efforts, but also looking to “re-architect” the way their systems collaborate by using this Data Lake environment to control and consolidate all information-sharing interactions within their environment. I was […]

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5 Oracle Analytics Trends to Watch Out for Starting Now

“Catching up” is the term that came to mind when I used to check out what’s new with Oracle Analytics in previous years. This year, however, I frankly say I was impressed with what I saw at Oracle Open World last week. The rules of the analytics platform game have changed, tremendously. This is after […]

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Webinar: The Role of Data Lakes in Healthcare

According to information technology research and advisory company Gartner, there is a market shift towards hybrid approaches to data management, as companies look to solve complex challenges with a mix of alternative and traditional deployments. Healthcare providers and health plans are asking the question, “Do we need an enterprise data warehouse, a data lake, or […]

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5 Ways to Build a Data Lake and not a Data Swamp

In the last 6 months, my customers and I have been on a journey with some of the largest cloud data lake vendors, open source Big Data vendors, and a team of the smartest Big Data architects that I’ve worked with in my career. As we explore this journey, often our clients are looking to […]

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Data Lakes vs Data Warehouses in Healthcare

In a recent post, Perficient’s Arvind Murali explained how the rise of Big Data and data lake technology is not an indication that traditional data warehousing is obsolete. There is a place for both solutions, since they address different challenges, and plenty of opportunities for integration as well. According to Gartner, there is a market […]

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Big Data and You: Data Agility

Welcome to “Big Data and You (the enterprise IT leader),” the Enterprise Content Intelligence group’s demystification of the “Big Data” . A critical piece of any DevOps or DataOps initiative is the processes, technology, and coordination which support it.  The Agile methodology, along with certain tools, can integrate various technical teams, along with business processes […]

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Lambda Architecture for Big Data – Quick peek…

In the Big Data world Lambda architecture created by Nathan Marz is a standard technique applied to solve many predictive analytics problems. This architecture effectively delivers the streaming data and batch data to combine the past information with the current changes, producing a comprehensive platform for predictive framework. Lambda Architecture On a very high generic […]

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One Cluster To Rule Them All!

In the Hadoop space we have a number of terms for the Hadoop File System used for data management. Data Lake is probably the most popular. I have heard it called a Data Refinery as well as some other not so mentionable names. The one that has stuck with me has been is the Data […]

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Data Staging and Hadoop

Traditionally, in our information architectures we have a number of staging or intermediate data storage areas / systems.   These have taken different forms over the years, publish directories on source systems, staging areas in data warehouses, data vaults, or most commonly, data file hubs.   In general, these data file staging solutions have suffered from two […]

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