article thumbnail

Pitching a DataOps Project That Matters

DataKitchen

DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. These benefits are hugely important for data professionals, but if you made a pitch like this to a typical executive, you probably wouldn’t generate much enthusiasm.

article thumbnail

Guidelines on Using Data Analytics for Finding the Right Price Points

Smart Data Collective

Data analytics technology is helping businesses boost profitability in many ways. A few years ago, Walter Baker and his colleagues at McKinsey reported that one of the biggest advantages of big data in business is that it can help with pricing decisions. How Can Data Analytics Help with Creating a Pricing Strategy?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Cloud analytics migration: how to exceed expectations

CIO Business Intelligence

A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making. Business objectives must be articulated and matched with appropriate tools, methodologies, and processes.

article thumbnail

Transforming Task Automation: The Future of Intelligent Orchestration

David Menninger's Analyst Perspectives

Moreover, seamless data integration supports real-time analytics, which enables swift and informed decision-making across the enterprise. Effective data management leads to improved insights into business processes that fuel innovation and strategic decision-making.

article thumbnail

My top learning and pondering moments at Splunk.conf22

Rocket-Powered Data Science

Observability is a business strategy: what you monitor, why you monitor it, what you intend to learn from it, how it will be used, and how it will contribute to business objectives and mission success. The key difference is this: monitoring is what you do, and observability is why you do it. This is what Splunk lives for!

article thumbnail

5 perspectives on modern data analytics

CIO Business Intelligence

Unfortunately, analytics initiatives seldom do nearly as well when it comes to stakeholder satisfaction. Pratt offered an excellent analysis of why data analytics initiatives still fail , including poor-quality or siloed data, vague rather than targeted business objectives, and clunky one-size-fits-all feature sets.

article thumbnail

Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.