Smart Data Collective

NOVEMBER 16, 2021

Text mining and text analysis are relatively recent additions to the data science world, but they already have an incredible impact on the corporate world. As businesses collect increasing amounts of often unstructured data, these techniques enable them to efficiently turn the information they store into relevant, actionable resources.

Analytics 119

Analytics Unstructured Data Data Collection Software 119

Smart Data Collective

MAY 1, 2022

Considering the amount of unstructured data produced daily, NLP has become integral to efficiently understanding and analyzing text—based data. Moreover, the data collected is not free from error or biases if humans handle it. Unstructured data can be difficult to skim through.

Cost-Benefit 117

Cost-Benefit Unstructured Data Machine Learning Marketing 117

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

SEPTEMBER 14, 2023

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 that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 134

Analytics Data Science Unstructured Data Data mining 134

Smart Data Collective

NOVEMBER 25, 2019

New technologies, especially those driven by artificial intelligence (or AI), are changing how businesses collect and extract usable insights from data. New Avenues of Data Discovery. Instead, they’ll turn to big data technology to help them work through and analyze this data.

Business Intelligence 102

Business Intelligence Predictive Analytics Data Collection Internet of Things 102

Cloudera

JUNE 9, 2022

With the rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.), controlling distribution while also allowing the freedom and flexibility to deliver the data to different services is more critical than ever. .

Data Collection 88

Data Collection IoT Data Lake Unstructured Data 88

DataRobot

NOVEMBER 2, 2021

RPA alone does not account for the decision process and often operates on the back of unstructured data. In the hiring process, traditional RPA accomplishes two tasks: job applicant data collection (e.g., But an intelligent RPA system—RPA coupled with the power of AI—can solve states’ hardest problems. The problem?

Unstructured Data 52

Unstructured Data Digital Transformation Data-driven Data Collection 52

Smart Data Collective

APRIL 5, 2022

This feature helps automate many parts of the data preparation and data model development process. This significantly reduces the amount of time needed to engage in data science tasks. A text analytics interface that helps derive actionable insights from unstructured data sets.

Cost-Benefit 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

Smart Data Collective

APRIL 29, 2021

It’s an incredible time in technology when data can be integrated to help predict how purchases are made, and major retailers such as Amazon and eBay already do this extremely well. Economists now have the ability to shift from small sample data sets and government surveys to much larger data collections.

Big Data 96

Big Data Forecasting Unstructured Data Statistics 96

Cloudera

FEBRUARY 8, 2021

The goal is to define, implement and offer a data lifecycle platform enabling and optimizing future connected and autonomous vehicle systems that would train connected vehicle AI/ML models faster with higher accuracy and delivering a lower cost.

Machine Learning 105

Machine Learning Manufacturing Unstructured Data Modeling 105

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 128

Analytics Data Science Statistics Unstructured Data 128

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

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.

Data Science 139

Data Science Statistics Machine Learning Visualization 139

IBM Big Data Hub

FEBRUARY 14, 2024

Using historical data of production, generative AI can predict or locate equipment failures in real time—and then suggest equipment adjustments, repair options or needed spare parts. Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

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 136

Management Internet of Things Statistics Data-driven 136

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

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.

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

Alation

SEPTEMBER 9, 2021

Banks collect and manage a lot of sensitive data. And, the data collection doesn’t stop there — rich insights like transactions and purchasing information help to round out customer profiles. In banks, this means: Setting data format standards. Tagging data types. Incorporating automation.

Data Governance 52

Data Governance Data Strategy Strategy Risk 52

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

Smart Data Collective

MARCH 24, 2020

Historically, the education system has accumulated a significant amount of data. Predicting academic performance is one of the key research topics in Big Data in education. A selection of information sources, data acquisition procedures, information processing algorithms. Data collection. Analysis of Indicators.

Big Data 100

Big Data Internet Publishing and Broadcasting Broadcasting Data Collection 100

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The global commercial drone market is projected to grow from USD 8.15

Data Collection 84

Data Collection Visualization Data-driven Unstructured Data 84

IBM Big Data Hub

SEPTEMBER 7, 2023

IBM’s watsonx AI and data platform lets you go beyond being an AI user and become an AI value creator.

Modeling 106

Modeling Risk Unstructured Data Enterprise 106

Domino Data Lab

JANUARY 21, 2021

First, I load the dataset and do a quick check to see the size of the data we’re working with: Note: the full dataset, with data collection back to 1987, is significantly larger than 300,000 samples. Working With Unstructured Data & Future Development Opportunities.

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

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 101

Digital Transformation Internet of Things Manufacturing Unstructured Data 101

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

AWS Big Data

FEBRUARY 1, 2024

It includes massive amounts of unstructured data in multiple languages, starting from 2008 and reaching the petabyte level. In the training of GPT-3, the Common Crawl dataset accounts for 60% of its training data, as shown in the following diagram (source: Language Models are Few-Shot Learners ). It is continuously updated.

Modeling 94

Modeling Metadata Data Processing Unstructured Data 94

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

Cloudera

AUGUST 20, 2021

Data Types and Sources: The multitude of data experiences enable efficient processing of different data types, such as structured and unstructured data collected from any potential source. A Robust Security Framework.

Strategy 94

Strategy Cost-Benefit Visualization Data Warehouse 94

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

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale.

Snapshot 82

Snapshot Data Lake Testing Strategy 82

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

datapine

NOVEMBER 19, 2019

This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience. Thus, deep nets can crunch unstructured data that was previously not available for unsupervised analysis.

Technology 279

Technology Internet of Things IT IoT 279

AWS Big Data

FEBRUARY 21, 2023

SQL Depth Runtime in Seconds Cost per Query in Seconds 14 80 40,000 12 60 30,000 5 30 15,000 3 25 12,500 The hybrid model addresses major issues raised by the data vault and dimensional model approaches that we’ve discussed in this post, while also allowing improvements in data collection, including IoT data streaming.

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

Sisense

JULY 23, 2021

This analytics engine will process both structured and unstructured data. “We We are constantly collecting data from all kinds of different sources — whether it is a library of documents, analytics reports, pictures, or even videos,” says Chris.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

datapine

FEBRUARY 22, 2022

Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Think of security, privacy, and compliance.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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. An effective data governance strategy is critical for unlocking the full benefits of this information.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52