Intro to AI, ML, DL – NLP and #DataVault 2.0
A look at how Data Vault Models can help Natural Language Processing, AI, ML, and DL algorithms.
Moving Beyond the Data-Driven Enterprise
By Cynthia Meyersohn, DataRebels LLC Do you really want your business or enterprise to be data–driven? Before you say, “Of course we do. Companies that do not embrace a data-driven approach to competition, market strategy, and process improvement will become extinct.” Understand, this is a trick question. The term data-driven has been around forever it
Solving the Time Crime of Back-Dated Data in Your Data Vault
Solving the Time Crime of Back-dated Data in Your Data Vault Analytics assumes that data movement will follow a linear path into a historical repository to represent the correct sequence of events. That is, if today is Thursday and we have loaded data for Wednesday, we then do not expect data from Tuesday to arrive
Bring Out Your Dead…Data
What plans are in place after you meet your demise? This subject is not a comfortable discussion to have for most. What happens to your belongings, your estate, and all that you leave behind? Who will be notified? And, what of those who depend on you? Graveyards paint a picture of dread in horror films and
Understanding Data Vault 2.0
Understanding #datavault 2.0, why DV2 is important, comparing with other data modeling methods, and how it works for #bigdata #iot, #streaming, #datawarehouse, and #datascience
Defining A Data Lake
Defining the Data Lake For too many years now, the definition of Data Lake has been muddy at best. The term has no clear definition in the industry. While many have tried, they have not (in my opinion) succeeded. I would judge success as being able to implement a Data Lake at an enterprise level