CIO Business Intelligence

SEPTEMBER 2, 2022

Tim Scannell: Data is a major focus of most IT organizations today — collecting it from a variety of sources, transforming it into business intelligence, getting it into the hands of the right people within the organization. How extensive is your data-driven strategy today? Khare: I look at uncertainty at two tiers.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

Management 75

Management Data Lake Uncertainty Data Warehouse 75

Sisense

JULY 6, 2020

Organizations are leaning on data and insights to navigate a new path forward as they deal with the crisis, but also as they reset their businesses. Analytics are essential in a crisis. Uncertainty often surfaces new opportunities as business leaders are forced to consider changes around key parts of the business.

Data-driven 81

Data-driven Uncertainty Reporting Predictive Analytics 81

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. Vignesh: Ganesh, you really highlighted some very important themes. These are strange times. And all at the same time. So, what do I mean by this? So, let’s say you are a CXO in a retail or consumer goods barring essentials.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Smarten

JULY 18, 2022

By incorporating analytics into day-to-day activities and allowing access for business users, the business can encourage the transition from business user to Citizen Data Scientist and create a comprehensive system of analytics with governance and collaboration to ensure security, appropriate access, mobile use and fact-based decision-making.

Uncertainty 52

Uncertainty Predictive Analytics Forecasting Analytics 52

Domino Data Lab

JUNE 2, 2019

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Rev 2 wrap up.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

CIO Business Intelligence

MARCH 30, 2022

Disruption and uncertainties will keep going for the following years, and being agile and resilient needs to become part of t the manufacturer’s DNA. This comes with building up data analytic capabilities, but it’s not necessarily about having an army of data scientists. Industry 4.0 for manufacturing.

Manufacturing 52

Manufacturing Uncertainty Digital Transformation Predictive Analytics 52

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Identify those most at risk or most affected by a problem more accurately by using predictive analytics.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43