CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Tableau: Now owned by Salesforce, Tableau is a data visualization tool.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

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 131

Analytics Data Science Statistics Unstructured Data 131

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

FineReport

JUNE 24, 2021

However, along with the diffusion of digital technology, the amount of data is getting larger and larger, and data collection and cleaning work have become more and more time-consuming. Once the data becomes more extensive or more complex, Excel or other simple solutions may “fetter” your potentialities.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

JUNE 28, 2022

And then there is the rise of privacy concerns around so much data being collected in the first place. Following are some of the dark secrets that make data management such a challenge for so many enterprises. Unstructured data is difficult to analyze.

Management 138

Management Internet of Things Statistics Data-driven 138

IBM Big Data Hub

AUGUST 28, 2023

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

CIO Business Intelligence

MARCH 29, 2022

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . An even larger issue is that people may not know how to see value in data.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Sisense

DECEMBER 12, 2019

Yet with this surge in data, many organizations are either not able to draw insights from their data, or are not able to do so quickly enough. It is estimated that of all data collected, less than 1% is actually analyzed and used. Your data is a gold mine and you’re barely scratching the surface of its value!

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

datapine

FEBRUARY 22, 2022

1) What Is A Business Intelligence Strategy? 4) How To Create A Business Intelligence Strategy. Odds are you know your business needs business intelligence (BI). Over the past 5 years, big data and BI became more than just data science buzzwords. Table of Contents.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

datapine

NOVEMBER 19, 2019

In business intelligence, we are evolving from static reports on what has already happened to proactive analytics with a live dashboard assisting businesses with more accurate reporting. This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience.

Technology 279

Technology Internet of Things IT IoT 279

FineReport

FEBRUARY 5, 2020

Nowadays, the business intelligence market is heating up. Both the investment community and the IT circle are paying close attention to big data and business intelligence. Overall, as users’ data sources become more extensive, their preferences for BI are changing. In the end.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Domino Data Lab

JANUARY 21, 2021

Additionally, the Python ecosystem is flush with open source development projects that maintain the language’s relevancy in the face of new techniques in the field of data science. It’s worth noting that there is a landscape of proprietary tools dedicated to producing descriptive analytics in the name of business intelligence.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Timo Elliott

JANUARY 22, 2019

2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

CIO Business Intelligence

JUNE 22, 2022

Digital infrastructure, of course, includes communications network infrastructure — including 5G, Fifth-Generation Fixed Network (F5G), Internet Protocol version 6+ (IPv6+), the Internet of Things (IoT), and the Industrial Internet — alongside computing infrastructure, such as Artificial Intelligence (AI), storage, computing, and data centers.

Digital Transformation 105

Digital Transformation Internet of Things Manufacturing Unstructured Data 105

AWS Big Data

FEBRUARY 21, 2023

It is a data modeling methodology designed for large-scale data warehouse platforms. What is a data vault? The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs.

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

Alation

DECEMBER 15, 2021

Modern business is built on a foundation of trusted data. Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. At the same time, it enhances data security and compliance programs.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

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. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52