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 93

Data Lake Snapshot Big Data Data-driven 93

FineReport

MAY 31, 2023

Contemporary dashboards surpass basic visualization and reporting by utilizing financial analytics to amalgamate diverse financial and accounting data, empowering analysts to delve further into the data and uncover valuable insights that can optimize cost-efficiency and enhance profitability.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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. This introduces the need for both polling and pushing the data to access and analyze in near-real time. We also used AWS Lambda for data processing. The data is partitioned on InputDataSetName, Year, Month, and Date.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JUNE 28, 2023

Challenges Customers across industries today are looking to increase revenue and customer engagement by implementing near-real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. ETL pipelines can be expensive to build and complex to manage. or higher).

Data Warehouse 85

Data Warehouse Analytics Metrics Dashboards 85

AWS Big Data

MARCH 21, 2024

Challenges Customers across industries today are looking to use data to their competitive advantage and increase revenue and customer engagement by implementing near real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more.

Data Warehouse 87

Data Warehouse Metrics Optimization Statistics 87

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. Amazon Redshift is straightforward to use with self-tuning and self-optimizing capabilities. Fault tolerance is built in. Create the S3 bucket and folder.

Analytics 96

Analytics Data Warehouse Testing Dashboards 96

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. You still need to set appropriate EMRFS retries to provide additional resiliency.

Data Lake 84

Data Lake Snapshot Metadata Optimization 84

AWS Big Data

FEBRUARY 13, 2023

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. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 67

Snapshot Data Warehouse Testing Analytics 67

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. Also consider the trade-offs. To get started, checkout the github repo.

Data Architecture 66

Data Architecture Metadata Data Lake Snapshot 66

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 69

Metadata Snapshot Data Warehouse Statistics 69

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 91

Data Lake Data Processing Metadata Snapshot 91

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 113

Data Lake Metadata Optimization Statistics 113

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. Key ways to optimize insights for sales. Daily snapshot of opportunities – a summary.

Sales 91

Sales Forecasting Snapshot Management 91

Corinium

APRIL 25, 2019

Most of my days focus on understanding what’s happening in the market, defining overall product strategy and direction, and translating into execution across the various teams. Then when there is a breach, it comes as a shock, “wow, I didn’t even know that application had access to so much sensitive data”. And then there is the Cloud.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

AUGUST 16, 2023

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. Iceberg also helps guarantee data correctness under concurrent write scenarios. Utilize Athena OPTIMIZE command to compact these small files.

Data Lake 71

Data Lake Metadata Testing Snapshot 71

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. Ricardo Serafim is a Senior AWS Data Lab Solutions Architect.

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 82

Machine Learning Metrics Management Big Data 82

AWS Big Data

MARCH 3, 2023

Cost optimization – When you run Spark or Hive applications using EMR Serverless, you pay for the amount of vCPU, memory, and storage resources consumed by your applications, leading to optimal utilization of resources. EMR Serverless includes the Amazon EMR performance-optimized runtime for Apache Spark and Hive.

Data Lake 83

Data Lake Dashboards Metrics Metadata 83

AWS Big Data

JUNE 21, 2023

A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80

Occam's Razor

APRIL 5, 2010

How to optimally leverage value based segmentation & Lifetime Value. There is a better way to analyze your acquisition strategy than simply using Conversion Rates or Cost Per Acquisition (CPA). Take a snapshot of your customer database for the past 2 years and it may look like this: That is an average. That's a $19.00

Analytics 135

Analytics Marketing Measurement Metrics 135

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

IBM Big Data Hub

SEPTEMBER 25, 2023

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively. But the simplicity ends there.

OLAP 93

OLAP Data Lake Data-driven Snapshot 93

Alation

AUGUST 26, 2021

Under an active data governance framework , a Behavioral Analysis Engine will use AI, ML and DI to crawl all data and metadata, spot patterns, and implement solutions. Data Governance and Data Strategy. In other words, leaders are prioritizing data democratization to ensure people have access to the data they need.

Metadata 64

Metadata Data Governance Dashboards Software 64