CIO Business Intelligence

JANUARY 20, 2023

Business intelligence vs. business analytics Business analytics and BI serve similar purposes and are often used as interchangeable terms, but BI should be considered a subset of business analytics. Business analytics, on the other hand, is predictive (what’s going to happen in the future?)

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

datapine

JANUARY 6, 2022

Based on that amount of data alone, it is clear the calling card of any successful enterprise in today’s global world will be the ability to analyze complex data, produce actionable insights and adapt to new market needs… all at the speed of thought. Business dashboards are the digital age tools for big data.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

OCTOBER 26, 2023

It’s a role that combines hard skills such as programming, data modeling, and statistics with soft skills such as communication, analytical thinking, and problem-solving. Business intelligence analyst resume Resume-writing is a unique experience, but you can help demystify the process by looking at sample resumes.

Business Intelligence 127

Business Intelligence Data-driven Statistics Data Warehouse 127

FineReport

JUNE 11, 2021

Also, we will give a brief introduction of what business analysts should do and the tools often used for BI&A. Business intelligence and analytics (BI&A) and the related field of big data analytics have emerged as an increasingly important area in the business communities. Business Analytics.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

Smart Data Collective

AUGUST 10, 2021

Data can help them create strategies based on these powerful forces. The good news is that it’s never been easier to collect and organize data. In the early days of analytics, only the largest companies could afford to leverage big data. But which tools are the most effective for businesses in 2021?

Analytics 132

Analytics Data-driven Data Science Advertising 132

Jen Stirrup

SEPTEMBER 19, 2019

360 Orlando and I’m presenting a workshop on From Business Intelligence to Business Analytics with the Microsoft Data Platform. Data becomes relevant for decision making when we start to use it properly, so this workshop will demonstrate the use of analytics for real-life use cases.

Business Analytics 40

Business Analytics Analytics Statistics Dashboards 40

Smart Data Collective

MAY 29, 2023

The rate of growth at which world economies are growing and developing thanks to new technologies in information data and analysis means that companies are needing to prepare accordingly. As a result of the benefits of business analytics , the demand for Data analysts is growing quickly.

Data Collection 104

Data Collection Big Data Statistics Software 104

Smart Data Collective

DECEMBER 14, 2021

More people are online today than ever before, so online tracking is inevitably used to obtain statistics and data for websites. Analyzing these statistics will help teams decide what needs to be addressed or what is working well for the site.

Data Collection 134

Data Collection Statistics Data-driven Marketing Analytics 134

datapine

MAY 16, 2019

Exclusive Bonus Content: Ready to use data analytics in your restaurant? Get our free bite-sized summary for increasing your profits through data! A sobering statistic if ever we saw one. Data offers the power to gain an objective, accurate, and comprehensive view of your restaurant’s daily functions.

Analytics 163

Analytics Predictive Analytics Advertising Dashboards 163

Rocket-Powered Data Science

JULY 14, 2023

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Analytics 166

Analytics Internet of Things Data Science Prescriptive Analytics 166

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Cloudera

NOVEMBER 2, 2020

Correlations across data domains, even if they are not traditionally stored together (e.g. real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). The extreme scale of “big data”, but with the feel and semantics of “small data”.

Data Warehouse 97

Data Warehouse Dashboards Optimization Interactive 97

FineReport

JUNE 11, 2021

Also, we will give a brief introduction of what business analysts should do and the tools often used for BI&A. Business intelligence and analytics (BI&A) and the related field of big data analytics have emerged as an increasingly important area in the business communities. Business Analytics.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

AWS Big Data

NOVEMBER 29, 2023

Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience. Learn more about the zero-ETL integrations, data lake performance enhancements, and other announcements below.

Data Warehouse 127

Data Warehouse Analytics Data Lake Machine Learning 127

Peter James Thomas

APRIL 9, 2019

These are as follows: General Data Articles. Data Visualisation. Statistics & Data Science. Analytics & Big Data. Data Visualisation. Statistics & Data Science. Data Science Challenges – It’s Deja Vu all over again! Analytics & Big Data.

Data-driven 49

Data-driven Statistics Data Science Big Data 49

Sisense

JUNE 26, 2019

For an enterprise company , that can mean building and maintaining data pipelines or optimizing database queries and anything in between. If you are a data engineer, then you know that data is your most valuable asset. The aged statistic still stands that 80% of your time will be spent preparing and optimizing data.

Enterprise 75

Enterprise Data Warehouse Dashboards Modeling 75

Peter James Thomas

AUGUST 2, 2019

Master Data – additional definition (contributor: Scott Taylor ). Reference Data (contributor: George Firican ). Statistics. Self-service (BI or Analytics). Management Information (MI). Optimisation. Robotic Process Automation.

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

FineReport

MARCH 24, 2024

Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis.

Statistics 52

Statistics Data mining Visualization Reporting 52

Peter James Thomas

AUGUST 12, 2018

I explore some similar themes in a section of Data Visualisation – A Scientific Treatment. Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7].

Statistics 49

Statistics Metrics Data Quality Measurement 49

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. For predictive analytics to deliver high accuracy, a lot depends on the combination of domain knowledge and technical expertise.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Predictive Analytics.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Sisense

JUNE 16, 2020

In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data. This piece was originally published on Search Business Analytics.

Analytics 69

Analytics Data-driven Sales Data Processing 69

Rita Sallam

JULY 22, 2016

Not sure about that, but Sisense is well suited for easily harmonizing, combining and modeling many different, complex and large data sets for fast interactive analysis. Sisense supports a wide range of relational, NoSQL and big data sources. Research VP, Business Analytics and Data Science.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Peter James Thomas

SEPTEMBER 19, 2018

The peterjamesthomas.com Data and Analytics Dictionary is an active document and I will continue to issue revised versions of it periodically. Data Asset. Data Audit. Data Classification. Data Consistency. Data Controls. Data Curation (contributor: Tenny Thomas Soman ).

Analytics 45

Analytics Testing Data Strategy Data Integration 45

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

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. What is the point of those obvious statistical inferences? Let’s define what these are.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Statistics 157

datapine

MAY 17, 2021

In the digital age, those who can squeeze every single drop of value from the wealth of data available at their fingertips, discovering fresh insights that foster growth and evolution, will always win on the commercial battlefield. Moreover, 83% of executives have pursued big data projects to gain a competitive edge.

Visualization 161

Visualization Data-driven Business Intelligence Dashboards 161

Jet Global

MAY 9, 2024

Financial services companies can use data pipelines to integrate and manage big data from multiple sources for historical trend analysis. Analyzing historical transaction data in financial reporting can help identify market trends and investment opportunities.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52