Smart Data Collective

APRIL 29, 2020

A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. The techniques for managing organisational data in a standardised approach that minimises inefficiency.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Know how to handle your data. Sirius can help.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

AWS Big Data

APRIL 19, 2023

This allows for a new way of thinking and new organizational elements—namely, a modern data community. However, today’s data mesh platform contains largely independent data products. Even with well-documented data products, knowing how to connect or join data products is a time-consuming job.

Technology 85

Technology Data-driven Machine Learning Sales 85

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

NOVEMBER 22, 2022

Identifying structured and unstructured data. Setting data management policies, like tagging data. A comprehensive data governance strategy ensures that you have quality data so you can leverage insights for data-driven decision making. Why Is Data Governance In The Public Sector Important?

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Octopai

OCTOBER 6, 2022

While the financial stress of migration is usually shouldered by company executives, the entire data team shares the stress of packing up data assets, moving them, unpacking them and putting them in the right locations, and hoping everything got there in one piece, with nothing broken or lost. Making moving easier. Ready, set, migrate!

Testing 52

Testing Visualization Data Transformation Strategy 52

Jet Global

MARCH 14, 2024

This straightforward and user-friendly access to source data makes it easier for your business users to examine and extract insights from your core data systems. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric.

Analytics 52

Analytics Management Reporting Enterprise 52

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. This method uses GZIP compression to optimize storage consumption and query performance. For Firehose stream name , enter a name (for this post, ProcessDevicePositionFirehose ).

Analytics 97

Analytics IoT Metadata Internet of Things 97

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

DataRobot Blog

MARCH 10, 2022

This is currently a widespread strategy across the industry where we are seeing companies move from reactive to predictive inventory management and capacity planning. The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

AWS Big Data

JULY 31, 2023

This concludes creating data sources on the AWS Glue job canvas. Next, we add transformations by combining data from these different tables. Transform the data Complete the following steps to add data transformations: On the AWS Glue job canvas, choose the plus sign. Choose Run to run the job.

Sales 52

Sales Data Warehouse Visualization Testing 52

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

Machine Learning 63

Machine Learning Data Warehouse Modeling Cost-Benefit 63

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Reporting 52

AWS Big Data

FEBRUARY 26, 2024

You simply configure your data sources to send information to OpenSearch Ingestion, which then automatically delivers the data to your specified destination. Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery.

Dashboards 64

Dashboards Testing Metrics Optimization 64

Ontotext

DECEMBER 9, 2020

This leads to lots of small data fetches to/from GraphDB over the network. As a side effect, the code performs unnecessary data transforms, joins and potentially requires your service architecture to employ cache mitigation strategies to reduce the inevitable latency. Now you can start using the SKOS GraphQL API.

Modeling 130

Modeling Management Optimization Metrics 130

AWS Big Data

MARCH 3, 2023

During the Build Lab, the customer will construct a prototype in their environment, using their data, with guidance on real-world architectural patterns and anti-patterns, as well as strategies for building effective solutions, from AWS service experts. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

Jet Global

MAY 1, 2023

Other money-making strategies include adding users in a per-seat structure or achieving price dominance in the market due. This strategy will ultimately increase sales, and prove a competitive advantage. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Domino Data Lab

AUGUST 20, 2019

So, if we need to dump some data, how do we do it? There are three major strategies: manual techniques based on our knowledge of the problem and the data, random sampling techniques that use coin flipping to keep or discard data, and model-based techniques that attempt to keep features that interact well with our learning model.

Testing 68

Testing Modeling Interactive Measurement 68