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 120

Data Lake Data Processing Metadata Snapshot 120

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 112

Optimization Snapshot Data Lake Metadata 112

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 340

Data Science Data Lake Data mining Deep Learning 340

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 61

Data Lake Metadata Cost-Benefit Data Warehouse 61

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. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93

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. availability.

Data Lake 87

Data Lake Snapshot Metadata Optimization 87

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 88

Data Lake Data Transformation Cost-Benefit Data-driven 88

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 76

Data Lake Snapshot Optimization Data Transformation 76

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 115

Data Lake Analytics Dashboards Metrics 115

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

NOVEMBER 17, 2023

Amazon Athena is a serverless, interactive analytics service built on open source frameworks, supporting open table file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. Let’s discuss some of the cost-based optimization techniques that contributed to improved query performance.

Optimization 114

Optimization Statistics Metadata Data Lake 114

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 71

Data Lake Cost-Benefit Dashboards Data Warehouse 71

AWS Big Data

NOVEMBER 29, 2023

This cloud service was a significant leap from the traditional data warehousing solutions, which were expensive, not elastic, and required significant expertise to tune and operate. Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse.

Data Warehouse 103

Data Warehouse Data Lake Analytics Machine Learning 103

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

Data Lake 84

Data Lake Statistics Data Architecture Finance 84

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. This introduces the need for both polling and pushing the data to access and analyze in near-real time.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Jet Global

SEPTEMBER 4, 2020

The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. Data Lakes. Traditional databases and data warehouses do not lend themselves to that task.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

NOVEMBER 13, 2023

Join the AWS Analytics team at AWS re:Invent this year, where new ideas and exciting innovations come together. For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. A shapeshifting guardian and protector of data like Data Lynx?

Analytics 111

Analytics Data Lake Data Warehouse Data-driven 111

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

Sisense

APRIL 9, 2021

Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. Analytics from your cloud data sources are key to transforming your business, but the reality of how most companies use them lags behind expectations. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Use AI to tackle huge datasets.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 83

Data Lake Data Governance Cost-Benefit Machine Learning 83

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems.

Data Lake 90

Data Lake Metadata Cost-Benefit Management 90

AWS Big Data

JUNE 20, 2023

Apache Iceberg is an open table format for very large analytic datasets. It 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. Mikhail specializes in data analytics services.

Data Lake 75

Data Lake Data Science Recreation/Entertainment Experimentation 75

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Microsoft. Azure Analysis Services.

Data Lake 110

Data Lake Analytics Data Warehouse Machine Learning 110

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

AWS Big Data

MARCH 26, 2024

We are delighted to announce the release of the Data Analytics Lens. Using the Lens in the Tool’s Lens Catalog, you can directly assess your Analytics workload in the console, and produce a set of actionable results for customized improvement plans recommended by the Tool. What’s new in the Data Analytics Lens?

Data Analytics 55

Data Analytics Analytics Big Data Data Lake 55

AWS Big Data

JANUARY 18, 2024

AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. Other AWS analytics services also support the user identity to be propagated.

Data Lake 92

Data Lake Metadata Data Governance Statistics 92

BizAcuity

JULY 13, 2021

Optimize your Go To Market: The gaming business consists of various applications like the gaming platforms (Casino, Live Dealer, Poker, Sports, Bingo, etc.), account platform, payment, affiliate, loyalty system, bonus and promotion systems, financial application, CRM system, and many others. Data Enrichment/Data Warehouse Layer.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Not only can resources be quickly provisioned and optimized for different workloads and processing needs, but it can be done cost effectively. The Problem with Hybrid Cloud Environments.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

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. For CoW tables, queries see the latest data committed.

Data Lake 95

Data Lake Snapshot Metadata Optimization 95

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. We wanted the team to try every idea even if 60% of them failed.”

Analytics 90

Analytics Data Lake Metadata Cost-Benefit 90

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

Data Analytics 123

Data Analytics Analytics Recreation/Entertainment Data Lake 123