CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Energy: Forecast long-term price and demand ratios.

Predictive Analytics 141

Predictive Analytics Analytics Predictive Modeling Forecasting 141

Smart Data Collective

NOVEMBER 1, 2020

k-means Clustering – Document clustering, Data mining. In data mining, k-means clustering is used to classify observations into groups of related observations with no predefined relationships. Hidden Markov Model – Pattern Recognition, Bioinformatics, Data Analytics. Source ].

Machine Learning 133

Machine Learning Data mining Visualization Statistics 133

Smart Data Collective

SEPTEMBER 16, 2020

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.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

Smart Data Collective

JUNE 19, 2022

Many suppliers are finding ways to use AI and data analytics more effectively. Finally, unexpected or unavoidable events, like the blockage of a major trade route or unprecedented and severe storms , can cause catastrophic delays that shut down manufacturing or prevent trade from coming or going to a region.

Risk 133

Risk Cost-Benefit Risk Management Manufacturing 133

Smart Data Collective

JUNE 29, 2022

You can make sure your email marketing strategy is even more cost-effective by investing in data analytics. A number of data mining tools make it easier to find quality content on the web, which you can use to optimize your own marketing strategy. This is the most important benefit of big data for email marketing.

Data-driven 136

Data-driven Marketing Cost-Benefit Big Data 136

Smart Data Collective

FEBRUARY 20, 2022

Only this way can you survive disruptive events – such as a global pandemic – various changes and remain relevant when new trends emerge. This is possibly one of the most important benefits of using big data. Data analytics technology helps companies make more informed insights. Making Decisions More Easily.

Big Data 111

Big Data Management Finance Data-driven 111

erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Smart Data Collective

FEBRUARY 28, 2022

Use Data Analytics to Craft the Perfect Social Media Management Strategy. Data analytics has made it a lot easier to manage your social media marketing strategies. You will be able to leverage analytics technology to see what strategies are performing the best. Big data is helping improve SEO strategies.

Big Data 98

Big Data Marketing Strategy Data-driven 98

BizAcuity

APRIL 28, 2019

Using algorithms, AI is now able to store data before making a prediction about something – such as when a debtor is likely to pay. And this data is crucial in taking the necessary steps to ensure successful debt collection. WNS is a leading utility company, which put predictive analytics to use.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

CIO Business Intelligence

MARCH 24, 2023

Varonis Data Governance Suite Varonis’s solution automates data protection and management tasks leveraging a scalable Metadata Framework that enables organizations to manage data access, view audit trails of every file and email event, identify data ownership across different business units, and find and classify sensitive data and documents.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Sisense

APRIL 26, 2020

Key points to keep in mind about semi-structured data: Falls under the heading of unstructured data, but it has some lower-degree organization (still falls short of relational databases) Can be coerced into useful and easy-to-leverage table formats Examples of semi-structured data include XML, JSON, Emails, NoSQL DBs, event tracking, and web pages.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

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

Cloudera

MAY 15, 2019

American Water leverages NiFi to track metrics against a simulated truck, showing the initial values in capturing this type of data. Walmart will be sharing about how its construction of a Finance stream in its data lake helped reduce and eliminate efforts on data mining and cleansing.

Enterprise 50

Enterprise Data Lake Data mining IoT 50

CIO Business Intelligence

DECEMBER 22, 2022

Research firm Gartner further describes the methodology as one focused on “improving the communication, integration, and automation of data flows between data managers and data consumers across an organization.” The approach values continuous delivery of analytic insights with the primary goal of satisfying the customer.

Analytics 127

Analytics Machine Learning Software Data mining 127

IBM Big Data Hub

JULY 24, 2023

It tracks four important pillars: metrics, events, logs and traces (MELT) to understand the behavior, performance, and other aspects of cloud infrastructure and apps. It aims to understand what’s happening within a system by studying external data.

IT 54

IT Analytics Cost-Benefit Predictive Analytics 54

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel.

Testing 152

Testing Metadata Dashboards Statistics 152

Jet Global

JUNE 29, 2020

High-level methods and tools project future trends, behaviors, and events, giving organizations the ability to put together “what-if” models and calculations in effort to future-proof aspects of their operations.

Analytics 98

Analytics Reporting Cost-Benefit Data mining 98

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. When it comes to data modeling, function determines form.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

NOVEMBER 30, 2017

They hold a series of well-attended industry events that focus advancing the art of modern analytics and big data. They have empowered countless companies to move beyond legacy reporting practices to lean, agile analytics practices. Big data platforms enable organizations to assemble data for a 360-degree view.

Strategy 40

Strategy Big Data Data mining Visualization 40

AWS Big Data

FEBRUARY 22, 2023

AWS Secrets Manager is an AWS service that can be used to store sensitive data, enabling users to keep data such as database credentials out of source code. Data analytic challenges As an ecommerce company, Ruparupa produces a lot of data from their ecommerce website, their inventory systems, and distribution and finance applications.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

BI-Survey

OCTOBER 23, 2019

New real-time security intelligence solutions are combining big data and advanced analytics to correlate security events across multiple data sources, providing early detection of suspicious activities, rich forensic analysis tools and highly automated remediation workflows. The most important current IT trends (n=332).

Big Data 49

Big Data Analytics Manufacturing Digital Transformation 49

Smarten

MAY 24, 2018

ElegantJ BI, an innovative vendor in Business Intelligence, Augmented Analytics and Augmented Data Preparation, is pleased to announce its participation in the Gartner 2018 INDIA Data & Analytics Summit from 5 – 6th June 2018 in Mumbai, India. ElegantJ BI is proud to be a Silver Sponsor at this important event.

Analytics 40

Analytics Data Analytics Data mining Predictive Modeling 40

datapine

NOVEMBER 27, 2019

That way, any unexpected event will be immediately registered and the system will notify the user. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. It’s an extension of data mining which refers only to past data.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. These pipelines help organizations maintain data quality and support informed decision-making across different domains. Privacy Policy.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

All of the above points to embedded analytics being not just the trendy route but the essential one. Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Standalone is a thing of the past. Privacy Policy.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52