what-is-exploratory-data-analysis 
Dataiku
MAY 17, 2022
Before building a model, an investigation of the data at hand is not only an ideal practice but a crucial phase of the data science lifecycle. A thorough, comprehensive understanding of your dataset(s) from the get-go is an absolute must for ensuring accurate analysis and insights further down the line.
TechCrunch
OCTOBER 28, 2020
We’ve seen our fair share of business intelligence (BI) platforms that aim to make data analysis accessible to everybody in a company. Most of them are still fairly complicated, no matter what their marketing copy says. and the bigger problem is that they don’t know what they don’t know.”
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CIO
MAY 1, 2023
The conversations reminded everyone that there isn’t a one-size-fits-all approach to the journey and that each organization should focus on its operating model, the architecture of the organization, and the availability, accessibility, and necessity for data to help inform the decision-making processes.
Cloudera
OCTOBER 4, 2023
Fast moving data and real time analysis present us with some amazing opportunities. Every organization has some data that happens in real time, whether it is understanding what our users are doing on our websites or watching our systems and equipment as they perform mission critical tasks for us.
Cloudera
JUNE 3, 2022
Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.
Mentormate
NOVEMBER 29, 2022
Increasingly, many of our clients ask us how they can make their organization data-driven. Why do they want to implement data solutions into their business in the first place? I’m here to talk about that “why” and, more specifically, one of the key outcomes that drive value when you successfully harness your data — actionable insights.
Cloudera
SEPTEMBER 22, 2022
We’ve previously highlighted opportunities to improve digital claims processing with data and AI. To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. Step one: gather the data. Utilizing a variety of data sources creates a more accurate picture of risks.
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