O'Reilly Media - Data
APRIL 11, 2018
It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.
CIO
DECEMBER 20, 2024
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Curate the data.
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CIO
DECEMBER 12, 2024
Business leaders may be confident that their organizations data is ready for AI, but IT workers tell a much different story, with most spending hours each day massaging the data into shape. Theres a perspective that well just throw a bunch of data at the AI, and itll solve all of our problems, he says.
TechCrunch
NOVEMBER 19, 2020
Data engineering is one of these new disciplines that has gone from buzzword to mission critical in just a few years. As data has exploded, so has their challenge of doing this key work, which is why a new set of tools has arrived to make data engineering easier, faster and better than ever.
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In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.
CIO
NOVEMBER 27, 2024
Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.
CIO
NOVEMBER 27, 2024
From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes.
Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale
Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. Given how data changes fast, there’s a clear need for a measuring stick for data and analytics maturity. Workshop video modules include: Breaking down data silos. Developing a data-sharing culture.
Speaker: Mindy Chen, Director of Decision Science, Hudl
There is no denying that growing a data team has its challenges. What you plan your data team structure to look like initially may not turn out to be the most effective long term. Building a well balanced skill set within your data team and evolving the function alongside the business to ensure continuous growth is no easy feat.
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