Yet2

FEBRUARY 7, 2024

yet2 employed their proprietary Big Data approach to quickly ingest and analyze thousands of data points across their database of 5,000+ CMOs, reducing the analysis time from months to days. yet2 ’s Big Data analysis was crucial for matching this information to the China CFDA database. Contact us at info@yet2.com

Big Data 59

Big Data Data Technical Review Marketing 59

Acuvate

JULY 15, 2022

While Azure Synapse Analytics and Snowflake are the most recommended tools for businesses that need to process large amounts of data, key differences will help you differentiate between the two and choose the best for your company’s needs. Azure Synapse Analytics vs. Snowflake: A Comparison. Azure Synapse Analytics?. Snowflake?.

Comparison 52

Comparison Big Data Data Tools 52

Brunner

JUNE 1, 2020

What do you estimate the “data maturity” of your organization to be? how difficult is it to navigate company silos and/or technology landscape to deliver the big data necessary for marketing and customer service purposes?). How well will your products and services perform in comparison?

Technical Review 40

Technical Review Data Comparison Agile 40

mjvinnovation

MAY 20, 2019

They can be grouped into four groups: Data visualization tools; Business Intelligence software; Self-service analysis platforms; Statistical analysis tools; Big Data Platforms. Often, it is at this stage that data is “cut into cubes” and different comparisons are made when trying to get actionable information.

Analysis 40

Analysis Data Big Data Groups 40

mjvinnovation

APRIL 29, 2019

In this context, access to open APIs permits the sharing of data between different insurers, startups, banks, InsurTechs (insurance startups based on technology, inspired by the Fintech model) and other organizations. What is the relationship between Open Insurance and Open Innovation?

Artificial Inteligence 40

Artificial Inteligence Open Innovation Data Analysis 40

Innovation 360 Group

SEPTEMBER 17, 2019

We have found a great deal of valuable insights in the data, particularly about top performing manufacturers. Figure 2 illustrates a comparison on 10 illustrative innovation capabilities between top quartile manufacturers and average companies. We use these as benchmarks to identify gaps and develop a roadmap for each organization.

Leadership 40

Leadership Artificial Inteligence Technology Culture 40

mjvinnovation

OCTOBER 5, 2020

Regardless of industry or size, organizations that want to remain competitive in the era of Big Data need to develop and efficiently implement Data Science capabilities – or risk being left behind. Do you know what Data Science is? One way to understand data science is to visualize what a data scientist does.

Data 52

Data Examples Artificial Inteligence Project 52