CIO Business Intelligence

JUNE 7, 2022

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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CIO Business Intelligence

MAY 28, 2022

In the first quarter of 2022, skills centered around “management, methodology, and process” were the most richly-rewarded, buoyed by demand for skills such as AIops, Azure Key Vault, big data analytics, complex event processing/event correlation, deep learning, DevSecOps, Google TensorFlow, MLOps, prescriptive analytics, PyTorch, Scaled Agile Framework (..)

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Rocket-Powered Data Science

MARCH 10, 2020

Incorporating context into the graph (as nodes and as edges) can thus yield impressive predictive analytics and prescriptive analytics capabilities. Context may include time, location, related events, nearby entities, and more.

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FineReport

APRIL 26, 2023

This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. With the right Big Data Tools and techniques, organizations can leverage Big Data to gain valuable insights that can inform business decisions and drive growth.

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Smart Data Collective

NOVEMBER 24, 2020

Business intelligence software will be more geared towards working with Big Data. Data Governance. One issue that many people don’t understand is data governance. It is evident that challenges of data handling will be present in the future too. Prescriptive Analytics.

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IBM Big Data Hub

NOVEMBER 20, 2019

In this blog post, we’ll share real-world stories of how decision optimization technology delivers prescriptive analytics capabilities and opens the door to operational efficiency. We will also introduce you to the IBM data science and AI platform solutions that can deliver operational efficiency that satisfies the business.

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IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Prescriptive analytics: Prescriptive analytics predicts likely outcomes and makes decision recommendations.

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Rocket-Powered Data Science

JULY 19, 2023

Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.

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BizAcuity

FEBRUARY 21, 2025

As AI becomes more sophisticated, its role in business intelligence will shift from reactive reporting to predictive and prescriptive analytics, empowering companies to make smarter, data-driven decisions that drive long-term growth. The companies that thrive in the coming years wont be the ones with the most data.

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CIO Business Intelligence

MAY 26, 2022

In the first quarter of 2022, skills centered around “management, methodology, and process” were the most richly-rewarded, buoyed by demand for skills such as AIops, Azure Key Vault, big data analytics, complex event processing/event correlation, deep learning, DevSecOps, Google TensorFlow, MLOps, prescriptive analytics, PyTorch, Scaled Agile Framework (..)

IT 98

IT Prescriptive Analytics Deep Learning Big Data 98

IBM Big Data Hub

JULY 27, 2022

Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications and performance-monitoring tools. Diagnostics to show why it happened.

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CDW Research Hub

MARCH 22, 2019

The solution helped make sense of an enormous amount of data about such things as member usage statistics, enrollment rates, contract and payment statuses, staffing and operations. empowering franchisees to use data for business decision-making, and. establishing a foundation for future predictive and prescriptive analytics.

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Data Warehouse Prescriptive Analytics Statistics Big Data 66

AWS Big Data

FEBRUARY 20, 2024

Clean up You may want to delete your S3 data and Redshift cluster if you are not planning to use it further to avoid unnecessary cost to your AWS account. In this post, we showcased how you can derive metrics from common atomic data elements from different data sources with unique schemas.

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Rocket-Powered Data Science

JULY 14, 2023

Along with the massive growth in sensor data (including location-based and time-based streaming data), there have emerged some special analytics categories that are growing in significance.

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Smarten

AUGUST 8, 2017

This is a small note on small data. I hope it has a big impact. The common understanding of the world is that one should use predictive and prescriptive data on big data. Predictive analytics like this allows pushing of right products to e-commerce shoppers.

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AWS Big Data

MARCH 26, 2024

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

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BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

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Cloudera

FEBRUARY 4, 2019

Streaming Analytics – Analyze millions of streams of data in real-time using advanced techniques such as aggregations, time-based windowing, content-filtering etc., to generate key insights and actionable intelligence for predictive and prescriptive analytics.

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IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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IBM Big Data Hub

JANUARY 25, 2024

Consider these questions: Do you have a platform that combines statistical analyses, prescriptive analytics and optimization algorithms? It can be if you rely on a spreadsheet, physical asset counts or solely on condition monitoring.

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Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? How is data analytics used in the travel industry?

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Domino Data Lab

JUNE 2, 2019

ans from Nick Elprin, CEO and co-founder of Domino Data Lab, about the importance of model-driven business: “Being data-driven is like navigating by watching the rearview mirror. If your business is using big data and putting dashboards in front of analysts, you’re missing the point.”. I consider that a healthy trend.

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IBM Big Data Hub

SEPTEMBER 30, 2022

Next, IBM Cognos Analytics with Watson is a trusted AI co-pilot for business decision-makers who want to improve the impact of their business function by empowering every user to turn data into insights, and rapidly make business decisions.

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IBM Big Data Hub

JANUARY 17, 2023

With this capability, not only can data-driven companies operationalize data science models on any cloud while instilling trust in AI outcomes, but they are also in a position to improve the ability to manage and govern the AI lifecycle to optimize business decisions with prescriptive analytics. Start a trial.

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FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis.

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datapine

NOVEMBER 27, 2019

4) Predictive And Prescriptive Analytics Tools. Business analytics of tomorrow is focused on the future and tries to answer the questions: what will happen? There are plenty of big data examples used in real life, shaping our world, be it in the buying experience or managing customers’ data.

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datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Prescriptive Analytics: What should we do? Mobile Analytics.

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Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?

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Andrew White

JANUARY 11, 2021

On end user clients calls, are you hearing a greater focus on use cases and greater need for prescriptive analytics, ex marketing analytics, sales analytics, healthcare, etc. where performance and data quality is imperative? Yes, prescriptive and predictive analytics remain very popular with clients.

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Jet Global

MAY 1, 2023

Ideally, your primary data source should belong in this group. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more.

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