By Fern Halper and Martin Pacino
Organizations are moving past traditional structured data and are embracing text data from emails, machine-generated data, and streaming data to enhance their analyses. Data science is an outgrowth of this of this evolution, but many companies are still in the early stages of their data science efforts. In this Ten Mistakes to Avoid, TDWI’s Fern Halper and Martin Pacino identify the mistakes most detrimental to building out a successful data science program.
File Type: .pdf
File Size: 437 KB
Duration: 15 pages
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By David Loshin
Despite the reams of material describing how to develop a data governance program, many continue to struggle with implementing a sustainable program that measurably meets the business objectives. Vacuous data policies, ill-defined roles and responsibilities, missing procedures for implementation, and an excessive fascination with tools all impede real progress in fully internalizing a data governance program.