AWS Big Data

MARCH 4, 2024

Apache Iceberg manages these schema changes in a backward-compatible way through its innovative metadata table evolution architecture. With Lake Formation, you can manage fine-grained access control for your data lake data on Amazon S3 and its metadata in the Data Catalog. Iceberg maintains the table state in metadata files.

Snapshot 124

Snapshot Data Lake Metadata Recreation/Entertainment 124

AWS Big Data

JUNE 10, 2024

A modern data strategy redefines and enables sharing data across the enterprise and allows for both reading and writing of a singular instance of the data using an open table format. The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data.

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

Smart Data Collective

AUGUST 25, 2020

Some of the benefits are detailed below: Optimizing metadata for greater reach and branding benefits. One of the most overlooked factors is metadata. Metadata is important for numerous reasons. Search engines crawl metadata of image files, videos and other visual creative when they are indexing websites.

Data mining 137

Data mining Metadata Big Data ROI 137

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Apache Iceberg addresses customer needs by capturing rich metadata information about the dataset at the time the individual data files are created.

Data Lake 128

Data Lake Data Processing Metadata Snapshot 128

AWS Big Data

OCTOBER 3, 2023

In-place data upgrade In an in-place data migration strategy, existing datasets are upgraded to Apache Iceberg format without first reprocessing or restating existing data. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files. Supported formats are Avro, Parquet, and ORC.

Data Lake 116

Data Lake Metadata Snapshot Recreation/Entertainment 116

Cloudera

FEBRUARY 22, 2022

In Iceberg, instead of listing O(n) partitions (directory listing at runtime) in a table for query planning, Iceberg performs an O(1) RPC to read the snapshot. It includes a catalog that supports atomic changes to snapshots – this is required to ensure that we know changes to an Iceberg table either succeeded or failed.

Snapshot 110

Snapshot Metadata Cost-Benefit Data Architecture 110

AWS Big Data

JANUARY 24, 2024

These formats enable ACID (atomicity, consistency, isolation, durability) transactions, upserts, and deletes, and advanced features such as time travel and snapshots that were previously only available in data warehouses. It will never remove files that are still required by a non-expired snapshot.

Snapshot 115

Snapshot Data Lake Metadata Optimization 115

Cloudera

FEBRUARY 14, 2024

This blog discusses a few problems that you might encounter with Iceberg tables and offers strategies on how to optimize them in each of those scenarios. You can take advantage of a combination of the strategies provided and adapt them to your particular use cases. You could also change the isolation level to snapshot isolation.

Optimization 59

Optimization Strategy Snapshot Metadata 59

AWS Big Data

MAY 24, 2023

You can adjust your retry strategy by increasing the maximum retry limit for the default exponential backoff retry strategy or enabling and configuring the additive-increase/multiplicative-decrease (AIMD) retry strategy. In that case, we have to query the table with the snapshot-id corresponding to the deleted row.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

Cloudera

NOVEMBER 13, 2020

The commonly-accepted best practice in database system design for years is to use an exhaustive search strategy to consider all the possible variations of specific database operations in a query plan. Unlike most traditional SQL databases, Impala eschews these exhaustive search query optimization strategies to simplify query planning.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

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. To develop your disaster recovery plan, you should complete the following tasks: Define your recovery objectives for downtime and data loss (RTO and RPO) for data and metadata.

Snapshot 81

Snapshot Data Warehouse Data Processing Strategy 81

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 95

Snapshot Data Lake Testing Strategy 95

AWS Big Data

JUNE 9, 2023

Iceberg doesn’t optimize file sizes or run automatic table services (for example, compaction or clustering) when writing, so streaming ingestion will create many small data and metadata files. Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query).

Data Lake 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

JULY 28, 2023

To successfully respond to a data subject’s requests, organizations should have a clear strategy to determine how data is forgotten, flagged, anonymized, or deleted, and they should have clear guidelines in place for data audits. Note that putting a comprehensive data strategy in place is not in scope for this post.

Snapshot 91

Snapshot Metadata Measurement Data Warehouse 91

Sisense

JANUARY 6, 2020

So, partnering with analysts to model Salesforce data will give sales teams more confidence to predict the revenue that teams are going to close at the end of any given period, and identify behaviors and strategies that will be most effective. Daily snapshot of opportunities that’s derived from a table of opportunities’ histories.

Sales 91

Sales Forecasting Snapshot Management 91

Cloudera

JULY 13, 2022

The service provides simple, easy-to-use, and feature-rich data movement capability to deliver data and metadata where it is needed, and has secure data backup and disaster recovery functionality. In this method, you prepare the data for migration, and then set up the replication plugin to use a snapshot to migrate your data.

Snapshot 91

Snapshot Management Cost-Benefit Metadata 91

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. Lake Formation permissions In Lake Formation, there are two types of permissions: metadata access and data access. Metadata access permissions allow users to create, read, update, and delete metadata databases and tables in the Data Catalog.

Data Architecture 73

Data Architecture Metadata Data Lake Snapshot 73

O'Reilly on Data

MARCH 20, 2019

They could also share their strategy with others, potentially leading to large losses for your company. Model documentation and explanation techniques : Model documentation is a risk-mitigation strategy that has been used for decades in banking. If you are using a two-stage model, be aware of an “allergy” attack.

Modeling 275

Modeling Machine Learning Predictive Modeling Consulting 275

Cloudera

JULY 13, 2023

A range of Iceberg table analysis such as listing table’s data file, selecting table snapshot, partition filtering, and predicate filtering can be delegated through Iceberg Java API instead, obviating the need for each query engine to implement it themself. The data files and metadata files in Iceberg format are immutable.

Metadata 70

Metadata Snapshot Data Warehouse Statistics 70

AWS Big Data

MARCH 10, 2023

You can simplify your data strategy by running multiple workloads and applications on the same data in the same location. Iceberg employs internal metadata management that keeps track of data and empowers a set of rich features at scale. One important aspect to a successful data strategy for any organization is data governance.

Data Lake 116

Data Lake Sales Data Warehouse Snapshot 116

Cloudera

JULY 14, 2023

Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration. In this blog, I will describe a few strategies one could undertake for various use cases. Query engines (Impala, Hive, Spark) might mitigate some of these problems by using Iceberg’s metadata files.

Snapshot 70

Snapshot Data Warehouse Metadata Testing 70

AWS Big Data

SEPTEMBER 13, 2023

The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker. Current snapshot – This table in the data lake stores latest versioned records (upserts) with the ability to use Hudi time travel for historical updates.

Data Lake 104

Data Lake Data Processing Metadata Snapshot 104

AWS Big Data

MAY 10, 2023

The cluster manager performs critical coordination tasks like metadata management and cluster formation, and orchestrates a few background operations like snapshot and shard placement. We concluded that allowing writes in this state should still be safe as long as it doesn’t need to update the cluster metadata.

Snapshot 108

Snapshot Testing Metadata Management 108

AWS Big Data

JULY 20, 2023

Additionally, partition evolution enables experimentation with various partitioning strategies to optimize cost and performance without requiring a rewrite of the table’s data every time. Metadata tables offer insights into the physical data storage layout of the tables and offer the convenience of querying them with Athena version 3.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

Alation

AUGUST 26, 2021

It includes intelligence about data, or metadata. The earliest DI use cases leveraged metadata — EG, popularity rankings reflecting the most used data — to surface assets most useful to others. Again, metadata is key. Data Governance and Data Strategy. Source: “What’s Your Data Strategy?”

Metadata 64

Metadata Data Governance Dashboards Software 64

AWS Big Data

FEBRUARY 1, 2023

Implementation strategy Based on these requirements, we changed strategies and started analyzing each issue to identify the solution. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JANUARY 8, 2024

Stream Processing – An application created with Amazon Managed Service for Apache Flink can read the records from the data stream to detect and clean any errors in the time series data and enrich the data with specific metadata to optimize operational analytics.

Analytics 124

Analytics IoT Data-driven Snapshot 124

AWS Big Data

FEBRUARY 13, 2023

This strategy aims to replicate a realistic workload in different RA3 cluster configurations and compare them with our DC2 configuration. To do this, we required the following: A reference cluster snapshot – This ensures that we can replay any tests starting from the same state. Take snapshot from 6 x RA3.4xlarge.

Snapshot 73

Snapshot Data Warehouse Analytics Testing 73

Cloudera

MAY 24, 2021

The age and hardware refresh cycle for legacy clusters is another important consideration when deciding on the in-place upgrade strategy. Second, configure a replication process to provide periodic and consistent snapshots of data, metadata, and accompanying governance policies. Once moved, disable them on the legacy cluster.

Metadata 83

Metadata Testing Snapshot Strategy 83

AWS Big Data

NOVEMBER 29, 2023

Materializations – Materializations are strategies for persisting dbt models in a warehouse. There are three strategies for incremental materialization. The merge strategy requires hudi , delta , or iceberg. With the other two strategies, append and insert_overwrite , you can use csv , parquet , hudi , delta , or iceberg.

Data Lake 117

Data Lake Management Metrics Data Warehouse 117

AWS Big Data

APRIL 3, 2024

By selecting the corresponding asset, you can understand its content through the readme, glossary terms , and technical and business metadata. By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes.

Data Quality 104

Data Quality Visualization Metadata Metrics 104

AWS Big Data

JANUARY 17, 2024

Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

Alation

JULY 28, 2022

There are tools to replicate and snapshot data, plus tools to scale and improve performance.” Those planning their migration to a cloud data warehouse would be wise to map out a strategy. You really need to understand the metadata and data definitions around different data sets,” Kirsch says. What do you migrate, how, and when?

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

Wayne Yaddow

MARCH 14, 2025

Snapshot testing augments debugging capabilities by recording past table states, facilitating the identification of unforeseen spikes, declines, or abnormalities before their effect on production systems. Workaround: Implement custom metadata tracking scripts or use dbt Clouds freshness monitoring.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

AWS Big Data

MARCH 3, 2023

If you need the individual column-level metadata to be available in the Data Catalog, run an AWS Glue crawler periodically to keep the AWS Glue metadata updated. You can choose an appropriate partitioning strategy on the S3 raw bucket for your use case.

Data Lake 91

Data Lake Dashboards Metrics Metadata 91

AWS Big Data

DECEMBER 9, 2024

Each branch has its own lifecycle, allowing for flexible and efficient data management strategies. This post explores robust strategies for maintaining data quality when ingesting data into Apache Iceberg tables using AWS Glue Data Quality and Iceberg branches. We discuss two common strategies to verify the quality of published data.

Data Quality 109

Data Quality Publishing Snapshot Data Lake 109

CIO Business Intelligence

MARCH 5, 2025

Decision Audit Trail a comprehensive logging strategy that records key data points (inputs, outputs, model version, explanation metadata, etc.) In-Processing Fairness Constraint strategies that incorporate fairness considerations directly into the model training process. associated with every decision made by the AI system.

Risk 121

Risk Risk Management Measurement Modeling 121