Ontotext

JULY 13, 2023

For example, offering more of the same product or content instead of complementary items Analytics tools that don’t really support decision making Chatbots that fail the Alan Turing test You name it! The customer and employee experience when using an application is key for companies to have a real impact on their processes and results.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

Smart Data Collective

SEPTEMBER 26, 2019

Unstructured data lacks a specific format or structure. As a result, processing and analyzing unstructured data is super-difficult and time-consuming. Semi-structured. Semi-structured data contains a mixture of both structured and unstructured data. Data Integration.

Big Data 80

Big Data Software Unstructured Data Data Integration 80

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

FineReport

JULY 18, 2022

Except for the rows and columns, you can also display your data through graphs and charts. For more advanced data analysis, Excel provides you with pivot tables, enabling you to analyze structured data through multiple dimensions quickly and effectively. Price: Excel is not a free tool. RapidMiner. From Talend.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

AWS Big Data

JULY 12, 2023

One of the key advantages of dbt is its ability to foster seamless collaboration within and across data analytics teams. A comprehensive testing framework ensures that your models consistently deliver accurate and reliable data, while modularity enables faster development via component reusability.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 79

Big Data Software Consulting Unstructured Data 79

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. This provides a solid foundation for efficient data integration.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Choose Save changes. Choose Confirm.

Sales 52

Sales Data Warehouse Visualization Testing 52

Alation

OCTOBER 28, 2021

This, in turn, empowers data leaders to better identify and develop new revenue streams, customize patient offerings, and use data to optimize operations. Storing the same data in multiple places can lead to: Human error: mistakes when transcribing data reduce its quality and integrity.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Metadata Management: In legacy implementations, changes to Data Products (e.g., Introduction.

Metadata 123

Metadata Cost-Benefit Enterprise Interactive 123

O'Reilly on Data

DECEMBER 19, 2018

have a large body of tools to choose from: IDEs, CI/CD tools, automated testing tools, and so on. are only starting to exist; one big task over the next two years is developing the IDEs for machine learning, plus other tools for data management, pipeline management, data cleaning, data provenance, and data lineage.

Machine Learning 261

Machine Learning Software Testing Metadata 261