The Data Roundtable

Data Management

Understand why managing your data is essential for analytics

Data Management

Dylan JonesJuly 2, 2015 0

Struggling with data governance alignment? Look to history.

If your organization is large enough, it probably has multiple data-related initiatives going on at any given time. Perhaps a new data warehouse is planned, an ERP upgrade is imminent or a data quality project is underway. Whatever the initiative, it may raise questions around data governance – closely followed by discussions about the

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Data Management

David LoshinJune 30, 2015 1

Data policies and data governance

In recent years, we practitioners in the data management world have been pretty quick to conflate “data governance” with “data quality” and “metadata.” Many tools marketed under "data governance" have emerged – yet when you inspect their capabilities, you see that in many ways these tools largely encompass data validation and data standardization. Unfortunately, we

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Data Management

Phil SimonJune 22, 2015 0

Is effective data governance possible in an era of big data?

.@philsimon on the new challenges of data governance.

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Data Management | Internet of Things

Man on smartphone considers data privacy concerns

Jim HarrisJune 18, 2015 0

ESP can determine if big data is eventful

Jim Harris says event stream processing determines if big data is eventful and relevant enough to process and store.

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Data Management

White paper cover for Understanding Data Streams in IoT

Joyce Norris-MontanariJune 15, 2015 0

Event stream processing – Tips 2 and 3: Understand the life cycle of the data, collection and consumption

Determining the life cycle of event stream data requires us to first understand our business and how fast it changes. If event data is analyzed, it makes sense that the results of that analysis would feed another process. For example, a customer relationship management (CRM) system or campaign management system like

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Data Management

Dylan JonesJune 11, 2015 0

Can ESP bridge the data quality gap?

As consumers, the quality of our day is all too often governed by the outcome of computed events. My recent online shopping experience was a great example of how computed events can transpire to make (or break) a relaxing event. We had ordered grocery delivery with a new service provider. Our existing provider

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Data Management

Joyce Norris-MontanariJune 9, 2015 0

Event stream processing – Tip 1: Don’t be overwhelmed

I believe most people become overwhelmed when considering the data that can be created during event processing. Number one, it is A LOT of data – and number two, the data needs real-time analysis. For the past few years, most of us have been analyzing data after we collected it,

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Data Management

David LoshinJune 4, 2015 0

Embedding event stream analytics

In my last two posts, I introduced some opportunities that arise from integrating event stream processing (ESP) within the nodes of a distributed network. We considered one type of deployment that includes the emergent Internet of Things (IoT) model in which there are numerous end nodes that monitor a set of sensors,

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Data Management

Jim HarrisJune 2, 2015 0

Three things that need to get real – real-time, that is

In my previous post, I discussed the similarities, differences and overlap between event stream processing (ESP) and real-time processing (RTP). In this post, I want to highlight three things that need to get real. In other words, three things that should be enhanced with real-time capabilities, whether it’s ESP, RTP or

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Data Management

David LoshinMay 27, 2015 0

Pushing event analytics to the edge

In my last post, we examined the growing importance of event stream processing to predictive and prescriptive analytics. In the example we discussed, we looked at how all the event streams from point-of-sale systems from multiple retail locations are absorbed at a centralized point for analysis. Yet the beneficiaries of those

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Data Management