CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

Business Intelligence 140

Business Intelligence Dashboards Data mining OLAP 140

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

FineReport

MARCH 24, 2024

The primary objective of a data analyst is to transform raw data into meaningful insights that drive organizational improvements. By conducting extensive research and analysis, they generate reports that inform strategic decisions, identify areas for enhancement, and guide the implementation of new initiatives.

Statistics 52

Statistics Data mining Visualization Reporting 52

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 122

Analytics Data Science Statistics Unstructured Data 122

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. Exclusive Bonus Content: How to be data driven in decision making? 3) Gather data now.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 101

Management Advertising Data Lake Sales 101

Domino Data Lab

JANUARY 21, 2021

This blog explores the challenges associated with doing such work manually, discusses the benefits of using Pandas Profiling software to automate and standardize the process, and touches on the limitations of such tools in their ability to completely subsume the core tasks required of data science professionals and statistical researchers.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 141

Management Advertising Data Lake Sales 141

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

APRIL 9, 2021

The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Here are the key stages: .

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

NOVEMBER 28, 2023

“By identifying and categorizing named entities, NER empowers data analysts and system engineers to unlock valuable insights from the vast data collected,” Minarik says. Ensure value with visualizations. The process of making unstructured data usable doesn’t end with analysis, Minarik says.

Unstructured Data 123

Unstructured Data Data-driven Visualization Data Quality 123

Rocket-Powered Data Science

SEPTEMBER 18, 2018

For the modern digital organization, the proof of any inference (that drives decisions) should be in the data! Rich and diverse data collections enable more accurate and trustworthy conclusions. Here is another example: suppose that a person goes to their doctor to report problems with painful headaches.

Big Data 103

Big Data Data Science Measurement Data Collection 103

datapine

APRIL 11, 2019

In the contemporary world of business, the age-old art of storytelling is far from forgotten: rather than speeches on the Senate floor, businesses rely on striking data visualizations to convey information, drive engagement, and persuade audiences. . Big data commands big stories. Start with data visualization.

Dashboards 169

Dashboards Visualization Data-driven Key Performance Indicator 169

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). A reference to a new phase in the Industrial Revolution that focuses heavily on interconnectivity, automation, Machine Learning, and real-time data. They cannot process language inputs generally.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Domino Data Lab

AUGUST 12, 2021

In this blog we will continue our discussion about data exploration with Pandas Profiler and include another tool that may come handy for those of us that may be more inclined to use visual clues, D-Tale. The purpose of Data Exploration. Data exploration is a very important step before jumping onto the machine learning wagon.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. ML model interpretability and data visualization. – back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. Free Download. From FineBI.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

DataRobot

OCTOBER 20, 2021

What Is Data Literacy? Data literacy is the ability to understand data science and AI applications critically using basic data visualization, communication, and reasoning skills. And beyond uniting diverse stakeholders, data literacy also empowers sectoral regulators to provide industry-specific guidance.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

NOVEMBER 22, 2022

From a data strategy perspective, the biggest trend is the need for IT teams to get clear visualization and insight in their applications irrespective of domain, whether on-premises, in the cloud or hybrid environments.” Understanding how to harvest and apply data can be a game-changer in many ways, Bishop states.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

MARCH 24, 2023

SAS Data Management Built on the SAS platform, SAS Data Management provides a role-based GUI for managing processes and includes an integrated business glossary, SAS and third-party metadata management, and lineage visualization. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Jet Global

AUGUST 14, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Better Data Culture. Good data warehouses should be reliable.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Sisense

SEPTEMBER 3, 2020

They are the link between the data resources available to an enterprise and executives looking for opportunities to make the business better, faster, and stronger. Data Analyst. Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

Data Science 101

OCTOBER 31, 2019

Therefore, learning some useful data mining procedures may prove beneficial in this regard. As taught in Data Science Dojo’s data science bootcamp , you will have improved prediction and forecasting with respect to your product. Data Collection. Deployment.

Data mining 77

Data mining KDD Data Science Forecasting 77

Jet Global

OCTOBER 2, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

IBM Big Data Hub

AUGUST 7, 2023

Therefore, IBM observes that more clients tend to consult AI leaders to help establish governance and enhance AI and data science capabilities, an operating model in the form of co-delivery partnerships. Impact Report Jan/Feb 2020; 22(1): New global recruitment performance benchmarks yield mixed results.

Optimization 57

Optimization Forecasting Data-driven Strategy 57

Domino Data Lab

MARCH 3, 2019

Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees. We had big surprises at several turns and have subsequently published a series of reports.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

AUGUST 15, 2023

Whether a project aims to improve suicide prevention using data science or to create new revenue streams by reimagining an organization’s core business, CIO 100 Award winners demonstrate the innovative spirit of today’s IT in the face of rapidly evolving organizational challenges.

IT 93

IT Manufacturing IoT Cost-Benefit 93

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Data Science meets Climate Science.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Cloudera

JANUARY 21, 2021

Does your organization’s success depend on immediate delivery of new reports, applications, or projects? This service enables ad-hoc data warehouse spin up, auto-scale, and auto-suspend to make ad-hoc analytics more cost-efficient and easily accessible to all. Your data warehouse is ready. Do you need faster time to value?

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. This is a very good thing.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. Some people seemed to be naturally good at doing this kind of high quality data analysis. Report noise/confidence First and foremost, we must be aware that randomness exists and will fool us.

Metrics 107

Metrics Measurement Statistics Data Collection 107