Smart Data Collective

APRIL 8, 2020

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. The data collected in the system may in the form of unstructured, semi-structured, or structured data.

Technology 133

Technology Data Warehouse Big Data Machine Learning 133

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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

JUNE 28, 2022

Text by itself doesn’t have much structure to begin with, but when you’ve got a pile of text written by hundreds or thousands of employees over dozens of years, then whatever structure there is might be even weaker. Even structured data is often unstructured.

Management 138

Management Internet of Things Statistics Data-driven 138

Cloudera

SEPTEMBER 29, 2021

Through processing vast amounts of structured and semi-structured data, AI and machine learning enabled effective fraud prevention in real-time on a national scale. . Data can be used to solve many problems faced by governments, and in times of crisis, can even save lives. .

Digital Transformation 79

Digital Transformation Data Governance Data-driven Uncertainty 79

Rocket-Powered Data Science

JULY 7, 2019

Such approaches can enable more accurate and faster modeling and analysis of the characteristics and behaviors of a system and can exploit data in intelligent ways to convert them to new capabilities, including decision support systems with the accuracy of full scale modeling, efficient data collection, management, and data mining.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Smart Data Collective

JUNE 11, 2019

With all of the information available today, many decisions can be driven by big data. The power of advanced data collection and monitoring systems means increasingly little guesswork when it comes to overall management strategy. A well-structured data management system can connect supply line communication.

Manufacturing 92

Manufacturing Analytics Big Data Data mining 92

IBM Big Data Hub

AUGUST 28, 2023

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis. positive, negative or neutral).

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

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. Query the data using Athena Athena is a serverless, interactive analytics service built to analyze unstructured, semi-structured, and structured data where it is hosted.

Analytics 92

Analytics IoT Metadata Internet of Things 92

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

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Ontotext

MAY 5, 2023

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. We think their adoption will bring benefits well beyond reporting.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

Peter James Thomas

AUGUST 29, 2018

Because I have an overseas postcode the guy at the checkout put dummy data into all the fields to get through the process quickly and not impact my customer experience, I desperately wanted to stop him but also wanted to catch my plane. This is where the process efficiency impacts good data collection.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

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 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

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

By dramatically lowering the cost of storing data for analysis, it ushered in an era of massive data collection. By changing the cost structure of collecting data, it increased the volume of data stored in every organization.

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

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. The time savings is massive and having an application that takes data security seriously is a huge benefit. Overall, the solution turns a massive data collection effort into a push-button activity.

Reporting 52

Reporting Enterprise Finance Business Analytics 52

Timo Elliott

JANUARY 22, 2019

Compliance drives true data platform adoption, supported by more flexible data management. As it has been for the last forty years, data collection, preparation, and standardization remain the most challenging aspects of analytics. Traditional analytics focused on structured data flowing from operational systems.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

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.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

Ontotext

MAY 18, 2020

Behind the scenes of linking histopathology data and building a knowledge graph out of it. Together with the other partners, Ontotext will be leveraging text analysis in order to extract structured data from medical records and from annotated images related to histopathology information.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

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

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.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

JANUARY 11, 2018

These companies were able to receive notable benefits from their data collection and aggregation efforts. Data Warehouses and data virtualization may offer some remedy but as it is pointed out in the research…. 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. While use of Sawzall at Google is in decline today, we believe the lessons discussed here have survived the test of time and are employed by descendant systems used throughout Google.

Data Science 56

Data Science Statistics Testing Metadata 56

Sisense

JULY 23, 2021

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

O'Reilly on Data

DECEMBER 19, 2018

Data management isn’t limited to issues like provenance and lineage; one of the most important things you can do with data is collect it. Given the rate at which data is created, data collection has to be automated. How do you do that without dropping data? Toward a sustainable ML practice.

Machine Learning 261

Machine Learning Software Modeling Testing 261