CIO Business Intelligence

NOVEMBER 19, 2024

Seamless data integration. The AI data management engine is designed to offer a cohesive and comprehensive view of an organization’s data assets. This unified approach is critical for the integration of data across on-premises settings, cloud environments, and hyperscaler platforms.

Management 116

Management Unstructured Data Deep Learning Metadata 116

AWS Big Data

JULY 29, 2024

This ensures that each change is tracked and reversible, enhancing data governance and auditability. History and versioning : Iceberg’s versioning feature captures every change in table metadata as immutable snapshots, facilitating data integrity, historical views, and rollbacks.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

AWS Big Data

APRIL 3, 2024

Manage your Iceberg table with AWS Glue You can use AWS Glue to ingest, catalog, transform, and manage the data on Amazon Simple Storage Service (Amazon S3). With AWS Glue, you can discover and connect to more than 70 diverse data sources and manage your data in a centralized data catalog. Nidhi Gupta is a Sr.

Data Lake 121

Data Lake Snapshot Metadata Data Architecture 121

AWS Big Data

JUNE 27, 2024

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. Amazon Redshift supports two kinds of snapshots: automatic and manual, which can be used to recover data. Snapshots are point-in-time backups of the Redshift data warehouse.

Snapshot 91

Snapshot Data Warehouse Data Processing Strategy 91

CIO Business Intelligence

MARCH 28, 2024

The integration enables a daily import of core financial and inventory data from Simphony into NetSuite, the company said, adding that this helps enterprises to consolidate financial reporting, streamline cash reconciliation, and eliminate time spent on manual data integrations.

Snapshot 105

Snapshot Sales Finance Enterprise 105

AWS Big Data

JUNE 10, 2024

Cost effectively maintaining Apache Iceberg tables Maintaining Apache Iceberg tables is crucial for optimizing performance, reducing storage costs, and ensuring data integrity. Expire snapshots Each write to an Iceberg table creates a new snapshot , or version, of a table.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

O'Reilly on Data

MARCH 20, 2019

Data integrity constraints: Many databases don’t allow for strange or unrealistic combinations of input variables and this could potentially thwart watermarking attacks. Applying data integrity constraints on live, incoming data streams could have the same benefits. Disparate impact analysis: see section 1.

Modeling 278

Modeling Machine Learning Predictive Modeling Consulting 278

AWS Big Data

OCTOBER 3, 2023

An in-place migration can be performed in either of two ways: Using add_files : This procedure adds existing data files to an existing Iceberg table with a new snapshot that includes the files. Unlike migrate or snapshot, add_files can import files from a specific partition or partitions and doesn’t create a new Iceberg table.

Data Lake 122

Data Lake Metadata Snapshot Recreation/Entertainment 122

Smart Data Collective

OCTOBER 19, 2022

But MongoDB also offers filesystem snapshot backups and queryable backups. DynamoDB is a bit more limited and complicated to manage as indexes are sized, billed, and provisioned separately from your data. Applications might end up handling stale data as global secondary indexes (GSIs) be inconsistent with underlying data.

Big Data 132

Big Data Management Recreation/Entertainment Cost-Benefit 132

AWS Big Data

MARCH 20, 2023

In this tutorial, we assume that the files are updated with new records every day, and want to store only the latest record per the primary key ( ID and ELEMENT ) to make the latest snapshot data queryable. Now your data integration job is authored in the visual editor completely. Choose Jobs. For Table name , enter ghcn.

Visualization 97

Visualization Data Lake Snapshot Big Data 97

AWS Big Data

NOVEMBER 22, 2023

Many AWS customers adopted Apache Hudi on their data lakes built on top of Amazon S3 using AWS Glue , a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.

Data Lake 115

Data Lake Snapshot Metadata Optimization 115

AWS Big Data

APRIL 6, 2023

Use the reindex API operation The _reindex operation snapshots the index at the beginning of its run and performs processing on a snapshot to minimize impact on the source index. The source index can still be used for querying and processing the data. See the following API command: POST _reindex?

Snapshot 113

Snapshot Recreation/Entertainment Strategy Metrics 113

AWS Big Data

OCTOBER 19, 2023

In this post, we discuss different architecture patterns to keep data in sync and up to date between data lakes built on open table formats and data warehouses such as Amazon Redshift. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0 For S3 Target location , enter s3:// / /hudi_incremental/ghcn/.

Data Lake 135

Data Lake Data Warehouse Visualization Snapshot 135

DataKitchen

MAY 10, 2021

These labor-intensive evaluations of data quality can only be performed periodically, so at best they provide a snapshot of quality at a particular time. DataOps automation that focuses on lowering the rate of errors ensures continuous testing and improvement in data integrity. Location Balance Tests.

Testing 214

Testing Manufacturing Data Quality Statistics 214

AWS Big Data

JULY 20, 2023

Using Apache Iceberg’s compaction results in significant performance improvements, especially for large tables, making a noticeable difference in query performance between compacted and uncompacted data. These files are then reconciled with the remaining data during read time.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

JUNE 27, 2023

Our previous solution offered visualization of key metrics, but point-in-time snapshots produced only in PDF format. Our client had previously been using a data integration tool called Pentaho to get data from different sources into one place, which wasn’t an optimal solution.

Metrics 98

Metrics Dashboards Interactive Visualization 98

Cloudera

MARCH 5, 2024

With built-in features like time travel, schema evolution, and streamlined data discovery, Iceberg empowers data teams to enhance data lake management while upholding data integrity. Zero Downtime Upgrades Beyond improvements to Iceberg and Ozone, the platform now boasts Zero Downtime Upgrades (ZDU).

Snapshot 87

Snapshot Data Lake Enterprise Data Governance 87

Jet Global

DECEMBER 19, 2019

However, if NetSuite financial teams are forced to export report data into Excel and spend hours reformatting it, or wait for power users or IT to work on their reporting, they struggle to meet required deadlines for reporting. Another key issue is the separation of report data from its source. They can’t easily do ad hoc reporting.

Reporting 59

Reporting Snapshot Finance Enterprise 59

AWS Big Data

DECEMBER 13, 2023

Using Amazon MSK, we securely stream data with a fully managed, highly available Apache Kafka service. Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Data Warehouse 115

Data Warehouse Snapshot Data Processing Internet of Things 115

AWS Big Data

JULY 19, 2023

We have identified the following numerical facts to measure: Quantity of tickets sold per sale Commission for the sale Implementing the Fact There are three types of fact tables (transaction fact table, periodic snapshot fact table, and accumulating snapshot fact table). Each serves a different view of the business process.

Modeling 92

Modeling Sales Data Warehouse Snapshot 92

Cloudera

SEPTEMBER 12, 2022

A data fabric answers perhaps the biggest question of all: what data do we have to work with? Managing and making individual data sources available through traditional enterprise data integration, and when end users request them, simply does not scale — especially in light of a growing number of sources and volume.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

AWS Big Data

NOVEMBER 10, 2023

This is particularly valuable for Type 2 slowly changing dimension (SCD) and timespan accumulating snapshot facts. Optimized Redshift queries – The Amazon Redshift integration for Apache Spark plays a crucial role in converting the Spark query plan into an optimized Redshift query.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111

IBM Big Data Hub

JULY 6, 2022

In addition to data observability, IBM clients can take advantage of use cases such as multicloud data integration, data governance and privacy, customer 360, and MLOps and trustworthy AI. Data observability will also integrate with these other use cases for improved results where both are applied.

Metadata 56

Metadata Data Quality Snapshot Cost-Benefit 56

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 1, 2023

AWS Glue for ETL To meet customer demand while supporting the scale of new businesses’ data sources, it was critical for us to have a high degree of agility, scalability, and responsiveness in querying various data sources. Every dataset in our system is uniquely identified by snapshot ID, which we can search from our metadata store.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 92

Metadata Data Architecture Machine Learning Cost-Benefit 92

Wayne Yaddow

MARCH 14, 2025

Users can apply built-in schema tests (such as not null, unique, or accepted values) or define custom SQL-based validation rules to enforce data integrity. dbt Core allows for data freshness monitoring and timeliness assessments, ensuring tables are updated within anticipated intervals in addition to standard schema validations.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

FineReport

MAY 31, 2023

The financial KPI dashboard presents a comprehensive snapshot of key indicators, enabling businesses to make informed decisions, identify areas for improvement, and align their strategies for sustained success. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

IBM Big Data Hub

JUNE 12, 2023

A long-standing partnership between IBM Human Resources and IBM Global Chief Data Office (GCDO) aided in the recent creation of Workforce 360 (Wf360), a workforce planning solution using IBM’s Cognitive Enterprise Data Platform (CEDP). Data quality is a key component for trusted talent insights.

Data Quality 63

Data Quality Data Governance People Analytics Data-driven 63

Jet Global

JANUARY 9, 2020

On one hand, BI analytic tools can provide a quick, easy-to-understand visual snapshot of what appears to be the bottom line. Here are two things that you absolutely need to understand before buying a BI analytics tool: BI tools can fool the naked eye. Good analytics exist outside of BI. BI Analytics Tools: Skin Deep Beauty?

Management 52

Management Analytics Visualization Dashboards 52

AWS Big Data

FEBRUARY 9, 2023

With scheduled flows, you can choose either full or incremental data transfer: With full transfer, Amazon AppFlow transfers a snapshot of all records at the time of the flow run from the source to the destination. He’s on a mission to make life easier for customers who are facing complex data integration challenges.

Data Warehouse 101

Data Warehouse Data-driven Snapshot Testing 101

Alation

JULY 28, 2022

“Cloud data warehouses can provide a lot of upfront agility, especially with serverless databases,” says former CIO and author Isaac Sacolick. There are tools to replicate and snapshot data, plus tools to scale and improve performance.” Migration leaders would be wise to filter out data, not to migrate via a clear policy.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 97

Management Metadata Internet of Things Testing 97

FineReport

JUNE 14, 2023

Additionally, the report presents daily sales revenue, which gives a snapshot of the revenue generated on a daily basis. Auditing your data sources helps streamline your efforts, ensuring that your reporting dashboard presents only the information and insights worth analyzing.

KPI 52

KPI Reporting Key Performance Indicator Sales 52

AWS Big Data

MAY 30, 2023

resource(“dynamodb”) table = dynamodb.Table(dydb_lookup_table) response = table.scan() items = response[“Items”] jsondata = sc.parallelize(items) lookupDf = glueContext.read.json(jsondata) return lookupDf # Load the Amazon Kinesis data stream from Amazon Glue Data Catalog. def readDynamoDb(): dynamodb = boto3.resource(“dynamodb”)

Data Lake 98

Data Lake Data Analytics Analytics Data Processing 98

Wayne Yaddow

FEBRUARY 26, 2025

Photo by Markus Spiske on Unsplash Introduction Senior data engineers and data scientists are increasingly incorporating artificial intelligence (AI) and machine learning (ML) into data validation procedures to increase the quality, efficiency, and scalability of data transformations and conversions.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

FineReport

JUNE 26, 2023

Managers can obtain an up-to-date snapshot of the project’s scope, time, cost, and quality parameters. This may include financial records, sales reports, customer feedback, or any other data that aligns with your performance objectives. Ensure the data is comprehensive and representative of the period or project under evaluation.

Reporting 52

Reporting Key Performance Indicator Sales Visualization 52