Smart Data Collective

AUGUST 18, 2021

Predictive analytics, in contrast, goes further than keyword scanning software by highlighting a plethora of valuable metrics like experience, job titles, qualifications, skills, industries, and businesses, and compares these to the open job description and even existing employee data. Finding the best fit for an open position.

Data Science 136

Data Science Management Big Data Metrics 136

Sisense

SEPTEMBER 9, 2019

We knew our journey with predictive analytics and sentiment analysis was going to be a gradual progression that would eventually help us understand and better serve our customers. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. It will be iterative.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

Jedox

OCTOBER 8, 2020

We are currently operating in an environment with a very high (if not the highest ever) level of VUCA, (Volatility, Uncertainty, Complexity, Ambiguity). The way you mitigate uncertainty is with planning, planning, and more planning. To quote General/President Dwight D.

Uncertainty 75

Uncertainty Cost-Benefit Unstructured Data Data-driven 75

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. What is paramount here is agility and resiliency,” Ory said.

Manufacturing 52

Manufacturing Uncertainty Digital Transformation Predictive Analytics 52

Smart Data Collective

MARCH 21, 2022

In the early days, organizations used a central data warehouse to drive their data analytics. Even today, there are a large number of them using data lakes to drive predictive analytics. In a centralized ecosystem, everyone is dependent upon everyone else thereby creating uncertainties and interrupted flow of accurate data.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

Sisense

JULY 6, 2020

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. With access to data insights, Soft Stuff was able to ideate, strategize, and launch a B2C consumer model within three weeks.

Data-driven 81

Data-driven Uncertainty Reporting Analytics 81

Cloudera

MARCH 2, 2018

Banking, transportation, healthcare, retail, and real estate, all have seen the emergence of new business models fundamentally changing how customers use their services. Identify those most at risk or most affected by a problem more accurately by using predictive analytics.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

Sisense

OCTOBER 6, 2020

These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. Now, how do you use signals from a pre-COVID world to predict a post-COVID demand scenario? Can we model the impact for such structural shocks? Vignesh: Ganesh, you really highlighted some very important themes.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” Predictive analytics, yeah, not so much.” Key highlights from the session include. Transcript. You can take TensorFlow.js

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

SEPTEMBER 2, 2022

I think we were always a data-driven organization, but what we are doing through AI and analytics is creating a rich data- and decision-making culture. The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. Khare: I look at uncertainty at two tiers.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

SEPTEMBER 2, 2022

I think we were always a data-driven organization, but what we are doing through AI and analytics is creating a rich data- and decision-making culture. The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. Khare: I look at uncertainty at two tiers.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Smart Data Collective

FEBRUARY 14, 2023

One of the biggest is that more financial institutions are using predictive analytics tools to assist with asset management. Predictive Asset Analytics, Riskalyze and Altruist are some of the tools that use predictive analytics to improve asset management for both individual and institutional investors.

Predictive Analytics 107

Predictive Analytics Management Analytics Risk 107

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