CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JUNE 28, 2022

For example, they may not be easy to apply or simple to comprehend but thanks to bench scientists and mathematicians alike, companies now have a range of logistical frameworks for analyzing data and coming to conclusions. More importantly, we also have statistical models that draw error bars that delineate the limits of our analysis.

Management 138

Management Internet of Things Statistics Data-driven 138

FineReport

MARCH 7, 2024

However, due to regulatory controls on sensitive data like phone numbers and technical challenges in cross-platform integration of Internet and mobile reporting data, our current matching rates are relatively low, reaching around 20% in ideal scenarios, excluding telecom data. Firstly, we establish a list of filtering criteria.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. In this model, the Lambda function is invoked for each incoming event. The Lambda function is triggered at regular intervals using a scheduled EventBridge rule.

Analytics 100

Analytics IoT Metadata Internet of Things 100

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. and constantly report this data to backend.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Ontotext

MAY 5, 2023

These two key data elements are used in approximately 80% of the use cases in the sector. It is reused in modeling the publication of entity data or regulatory-mandated data exchange, as seen in the example provided below. Integrating reporting to move to a more streamlined, efficient approach to data collection.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

Alation

MAY 16, 2023

It’s worth noting that a data pipeline may have more than one data source. Data Collection Data collection, sometimes called data ingestion, is the process of moving data into the data pipeline. Ingestion tools are connected to various data sources.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Peter James Thomas

AUGUST 29, 2018

What I would say is that there is no “one size fits all” approach to the CDO organisation model. It depends on the company culture and structure and it needs to fit with the stated objectives of the role as designed. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

AWS Big Data

MARCH 26, 2024

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. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

Alation

MAY 16, 2023

It’s worth noting that a data pipeline may have more than one data source. Data Collection Data collection, sometimes called data ingestion, is the process of moving data into the data pipeline. Ingestion tools are connected to various data sources.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

erwin

APRIL 18, 2019

Under the GDPR, organizations must make any personal data collected from an EU citizen available upon request. CCPA compliance only requires data collected within the last 12 months to be shared upon request. Analyze data: Understand how data relates to the business and what attributes it has.

Data Governance 81

Data Governance Metadata Data-driven Data Collection 81

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

FineReport

JUNE 24, 2021

Originally, Excel has always been the “solution” for various reporting and data needs. 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. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

FineReport

FEBRUARY 5, 2020

Some people pay attention to functions and interaction effects, such as data collection, image and video collection, positioning, linkage and drilling on the mobile devices. However, please pay more attention to the security of mobile terminals, and mobile BI must ensure the security of corporate data.

Metadata 98

Metadata Dashboards Informatics Visualization 98

FineReport

JULY 18, 2022

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. Price: Excel is not a free tool. Python enjoys strong portability.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

IBM Big Data Hub

NOVEMBER 30, 2022

Switching to IBM Business Analytics gave Jabil the ability to gather and structure data to provide a central approach to management. They had a small IT team and needed a powerful tool that could handle a variety of uses, like tax provisioning in treasury, reporting and modeling for finance and still scale.

Reporting 52

Reporting Enterprise Finance Business Analytics 52

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. Who builds their models? Management.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Ontotext

MAY 18, 2020

Such problems and the complexities related to such computationally-intensive tasks are essential in the fields of weather forecasting, molecular modeling, airplane and spacecraft aerodynamics, personalized medicine, self-driving cars. Behind the scenes of linking histopathology data and building a knowledge graph out of it.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Cloudera

JANUARY 11, 2018

Data science and advanced analytics deliver more value if organizations can deploy models and algorithms on detailed data brought together from many sources, not just on summaries or samples contained in a single data warehouse or data mart.” ” And teases at the reward. You can too, as David describes….

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Sawzall is a programming language developed at Google for performing aggregation over the result of complex operations on structured data. Another potential issue, specific to SQL, is that the rich structure of the protobuf might not lend itself to an intuitive relational model.

Data Science 56

Data Science Statistics Testing Metadata 56

Sisense

JULY 23, 2021

While data and analytics are nothing new to the Olympics — they’ve been used in some form or another for many, many years — what is new is the importance of using data to manage the evolving changing models for delivery of the Games,” Chris says. >>>Infused Using data to create a more modern Olympics.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Metadata Testing 261

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52