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. Predictive analytics to show what will happen next.

Prescriptive Analytics 93

Prescriptive Analytics Descriptive Analytics Data-driven Cost-Benefit 93

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

FineReport

APRIL 26, 2023

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. What is Big Data? What is Big Data? It is an ever-expanding collection of diverse and complex data that is growing exponentially.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Smarten

JUNE 2, 2017

From reporting to visualised dashboard to predictive analytics. We know that by designing self-learning programs, we are in a position to provide prescriptive analytics. Some prescriptive analytics based on known parameters were always a part of ERP or BI offering. This was early predictive or was it?

Business Intelligence 40

Business Intelligence Visualization Prescriptive Analytics Predictive Analytics 40

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.

Data Strategy 100

Data Strategy Strategy Data Warehouse Prescriptive Analytics 100

Jedox

JULY 31, 2018

Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive. Analytic Evolution in Enterprise Performance Management. Advanced analytics responds to next-generation requirements.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

Sisense

AUGUST 11, 2019

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. Or is Business Intelligence One Part of Business Analytics?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

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

Sisense

SEPTEMBER 12, 2019

We’ve even gone as far as saying that every company is a data company , whether they know it or not. And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business. 3 Define how the data will be shared (and how it will be distributed).

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

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

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

datapine

NOVEMBER 27, 2019

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. 4) Predictive And Prescriptive Analytics Tools.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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?

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

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?

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Statistics 157

Smarten

JULY 30, 2024

‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’ That’s why your business needs predictive analytics. And, not just any predictive analytics!

Predictive Analytics 64

Predictive Analytics Prescriptive Analytics Predictive Modeling Analytics 64

Andrew White

JANUARY 11, 2021

Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. 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. Governance.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Smarten

SEPTEMBER 9, 2024

‘To fulfill the role of a Citizen Data Scientist, business users today can leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.’

Prescriptive Analytics 52

Prescriptive Analytics Predictive Analytics Data-driven Business Intelligence 52

Smarten

SEPTEMBER 9, 2024

What is a Cititzen Data Scientist? Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’ Who is a Citizen Data Scientist?

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

Jet Global

MAY 1, 2023

Third-party data might include industry benchmarks, data feeds (such as weather and social media), and/or anonymized customer data. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing. Diagnostic Analytics: No longer just describing.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52