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. In summary, this is an exciting time.

Machine Learning 107

Machine Learning Manufacturing Unstructured Data Modeling 107

Smart Data Collective

APRIL 5, 2022

IBM Watson Studio is a very popular solution for handling machine learning and data science tasks. Companies working on AI technology can use it to improve scalability and optimize the decision-making process. This feature helps automate many parts of the data preparation and data model development process.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

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

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. The average salary for a data engineer is $118,915 per year, with a reported salary range of $87,000 to $177,000 per year, according to data from Glassdoor.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. The average salary for a data engineer is $118,915 per year, with a reported salary range of $87,000 to $177,000 per year, according to data from Glassdoor.

Finance 98

Finance IT Software Reporting 98

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 92

Data Collection IoT Data Lake Unstructured Data 92

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 processes and methodologies.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

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 60

Data mining Machine Learning Deep Learning Marketing 60

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

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 101

Big Data Internet Publishing and Broadcasting Broadcasting Data Collection 101

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. In a nutshell, DaaS provides simplified asset and value optimization.

Data Collection 86

Data Collection Visualization Data-driven Unstructured Data 86

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

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 Holistic Visual Exploration of Data. A Robust Security Framework.

Strategy 96

Strategy Cost-Benefit Visualization Data Warehouse 96

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

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 85

Snapshot Data Lake Testing Strategy 85

FineReport

FEBRUARY 5, 2020

To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department. 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.

Metadata 98

Metadata Dashboards Informatics Visualization 98

datapine

NOVEMBER 19, 2019

There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. 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

AWS Big Data

FEBRUARY 21, 2023

We dive deep into a hybrid approach that aims to circumvent the issues posed by these two and also provide recommendations to take advantage of this approach for healthcare data warehouses using Amazon Redshift. What is a dimensional data model? It optimizes the database for faster data retrieval. What is a hybrid model?

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Modeling 65

Sisense

JULY 23, 2021

We focus on the core games management systems, which generate a lot of key operational data, so we’ve been naturally a lot more inquisitive of those datasets. We are focused on unpicking them, really analyzing them to understand what they tell us about Games optimization.”. The results have been highly valuable.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

datapine

FEBRUARY 22, 2022

In the article, he pointed to a pretty fascinating trend: “Experian has predicted that the CDO position will become a standard senior board-level role by 2020, bringing the conversation around data gathering, management, optimization, and security to the C-level.” We love that data is moving permanently into the C-Suite.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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 66

Data Architecture Data Lake Machine Learning Data Governance 66

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. . CRM platforms).

Data Processing 91

Data Processing Data Warehouse Enterprise Visualization 91

Jet Global

MAY 9, 2024

ELT can simplify the data pipeline by reducing the number of steps and tools involved, but it may rely on the destination system’s ability to handle complex transformations effectively. In an ETL process, data transformations can be optimized before loading, which may improve performance for data-intensive transformations.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52