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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

During the product launch, everyone in the sales and marketing organizations is hyper-focused on business development. Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. The data team must be able to respond rapidly and with a high degree of quality and certainty to user requests.

Analytics 246
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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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DataOps For Business Analytics Teams

DataKitchen

Customers and market forces drive deadlines and timeframes for analytics deliverables regardless of the level of effort required. Business analytic teams field an endless stream of questions from marketing and salespeople and they can’t get ahead. Business analysts live under constant pressure to deliver.

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How to rule your data world: The role of data governance

BI-Survey

With the growing interconnectedness of people, companies and devices, we are now accumulating increasing amounts of data from a growing variety of channels. New data (or combinations of data) enable innovative use cases and assist in optimizing internal processes.

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How The CIO Can Become The CMO’s Best Ally In The Use Of Data

CIO Business Intelligence

However, as data enablement platform, LiveRamp, has noted, CIOs are well across these requirements, and are now increasingly in a position where they can start to focus on enablement for people like the CMO. Marketing should not have access to elements of the finance team’s data, for example.

Risk 105
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Introducing watsonx: The future of AI for business

IBM Big Data Hub

A foundation model thus makes massive AI scalability possible, while amortizing the initial work of model building each time it is used, as the data requirements for fine tuning additional models are much lower. This results in both increased ROI and much faster time to market.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

This means you can seamlessly combine information such as clinical data stored in HealthLake with data stored in operational databases such as a patient relationship management system, together with data produced from wearable devices in near real-time. We use on-demand capacity mode.