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. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. The Data Catalog provides a central location to govern and keep track of the schema and metadata.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

CIO Business Intelligence

MAY 16, 2022

The advent of distributed workforces, smart devices, and internet-of-things (IoT) applications is creating a deluge of data generated and consumed outside of traditional centralized data warehouses. billion connected IoT devices by 2025, generating almost 80 billion zettabytes of data at the edge. “The

IoT 95

IoT Data Warehouse Internet of Things Machine Learning 95

AWS Big Data

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Jet Global

APRIL 20, 2020

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Such BI methodologies are built on a snapshot of what happened in the past.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

AWS Big Data

JANUARY 17, 2024

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. By identifying these changes, the query engine can optimize the query to process only the relevant data, significantly reducing the processing time and resource requirements.

Data Lake 89

Data Lake Snapshot Big Data Data-driven 89

Cloudera

APRIL 3, 2023

Cloudera Contributors: Ayush Saxena, Tamas Mate, Simhadri Govindappa Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg. We will publish follow up blogs for other data services.

Data Warehouse 78

Data Warehouse Snapshot Metadata Cost-Benefit 78

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Next, we create an S3 bucket.

Analytics 92

Analytics Data Warehouse Testing Dashboards 92

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JUNE 28, 2023

In this post, we provide step-by-step guidance on how to get started with near-real time operational analytics using this feature. There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g.

Data Warehouse 81

Data Warehouse Analytics Metrics Dashboards 81

Cloudera

FEBRUARY 8, 2024

Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. Starting from the CDW Public Cloud DWX-1.6.1

Snapshot 87

Snapshot Metadata Cost-Benefit Data Warehouse 87

IBM Big Data Hub

APRIL 8, 2024

Answer : Along with standard RDS features, Amazon RDS for Db2 supports key Db2 features, such as row and column organized tables for mixed and analytic workloads, the Adaptive Workload Optimizer to for better resource management, and rules-based access controls for advanced data protection.   13.

Snapshot 77

Snapshot Data Warehouse Data Processing Management 77

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs).

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

JULY 27, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Take a snapshot of the source Redshift data warehouse.

Testing 63

Testing Data Warehouse Data Processing Snapshot 63

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

Data Lake 89

Data Lake Snapshot Metadata Optimization 89

AWS Big Data

FEBRUARY 13, 2023

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data.

Snapshot 64

Snapshot Data Warehouse Testing Analytics 64

AWS Big Data

MARCH 21, 2024

In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation of the zero-ETL series that started with Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift.

Data Warehouse 84

Data Warehouse Metrics Optimization Statistics 84

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. This property is set to true by default. AIMD is supported for Amazon EMR releases 6.4.0 Jupyter Enterprise Gateway 2.6.0,

Data Lake 80

Data Lake Snapshot Metadata Optimization 80

AWS Big Data

APRIL 27, 2023

Apache Iceberg is an open table format for data lakes that manages large collections of files as tables. It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. However, this requires knowledge of a table’s current snapshots.

Data Lake 70

Data Lake Snapshot Optimization Data Transformation 70

AWS Big Data

OCTOBER 20, 2023

You can have multiple internal applications such as databases, data warehouses, or other systems where DNS names are not publicly resolvable. You can now use MSK Connect to privately connect with databases, data warehouses, and other resources in your VPC to comply with your security needs.

Data Processing 83

Data Processing Snapshot Data Warehouse Management 83

Cloudera

JULY 13, 2023

Iceberg is an emerging open-table format designed for large analytic workloads. Several compute engines such as Impala, Hive, Spark, and Trino have supported querying data in Iceberg table format by adopting this Java Library provided by the Apache Iceberg project. The data files and metadata files in Iceberg format are immutable.

Metadata 69

Metadata Snapshot Data Warehouse Statistics 69

AWS Big Data

JANUARY 24, 2023

Data migration must be performed separately using methods such as S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication. This utility has two modes for replicating Lake Formation and Data Catalog metadata: on-demand and real-time. Nivas Shankar is a Principal Product Manager for AWS Lake Formation.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. For Task logs , enable Turn on CloudWatch logs and Turn on batch-optimized apply. Before joining AWS, Manish’s experience includes helping customers implement data warehouse, BI, data integration, and data lake projects.

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

AWS Big Data

OCTOBER 24, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud, providing up to five times better price-performance than any other cloud data warehouse, with performance innovation out of the box at no additional cost to you. Ranjan Burman is a Analytics Specialist Solutions Architect at AWS.

Metrics 81

Metrics Statistics Data Warehouse Cost-Benefit 81

Cloudera

MAY 13, 2021

WM simplifies troubleshooting failed jobs and optimizing slow jobs. In this blog, we walk through the Impala workloads analysis in iEDH, Cloudera’s own Enterprise Data Warehouse (EDW) implementation on CDH clusters. After moving to CDP, take a snapshot to use as a CDP baseline. Batched and scripted.

Management 68

Management Data Warehouse Interactive Reporting 68

Sisense

JANUARY 6, 2020

Analytics and sales should partner to forecast new business revenue and manage pipeline, because sales teams that have an analyst dedicated to their data and trends, drive insights that optimize workflows and decision making. This is not to say that data modeling should be focused specifically on sales.

Sales 91

Sales Forecasting Snapshot Management 91

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Why should Chief Data & Analytics Officers care about data security?

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

AUGUST 16, 2023

Apache Iceberg is an open table format for very large analytic datasets. Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Utilize Athena OPTIMIZE command to compact these small files.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

Cloudera

SEPTEMBER 12, 2022

Once you have the access to all the data you need at the right time, the next step is to be able to use the data efficiently, opening the door for new analytic use cases. This is where the data lakehouse comes in. Cloudera has supported data lakehouses for over five years. Better together.

Unstructured Data 71

Unstructured Data Data Architecture Data Lake Snapshot 71

Occam's Razor

APRIL 5, 2010

How to optimally leverage value based segmentation & Lifetime Value. Take a snapshot of your customer database for the past 2 years and it may look like this: That is an average. You'll work with your acquisition team or your finance team to get the cost data. Optimizing acquisition channels with LTV.

Analytics 135

Analytics Marketing Measurement Metrics 135

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. Enterprise Data Engineering From the Ground Up. A Technical Look at CDP Data Engineering.

Visualization 101

Visualization Metrics Statistics Optimization 101

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 79

Machine Learning Metrics Management Big Data 79

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

AWS Big Data

JUNE 21, 2023

Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse. To house our data, we need to define a data model.

Data Warehouse 76

Data Warehouse Data Lake OLAP Cost-Benefit 76