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

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. It will never remove files that are still required by a non-expired snapshot.

Snapshot 100

Snapshot Data Lake Metadata Optimization 100

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. We use a sample JSON file as input to Amazon DynamoDB.

Data Lake 69

Data Lake Metadata Testing Snapshot 69

AWS Big Data

DECEMBER 21, 2023

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

Data Lake 88

Data Lake Data Warehouse Data-driven B2B 88

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 97

Data Lake Data Warehouse Machine Learning Cost-Benefit 97

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 92

Data Lake Data Warehouse Machine Learning Cost-Benefit 92

AWS Big Data

MAY 1, 2024

To provide a variety of products, services, and solutions that are better suited to customers and society in each region, we have built business processes and systems that are optimized for each region and its market. However, Excel is mainly designed for spreadsheets; it’s not designed for large-scale data analytics and automation.

Dashboards 111

Dashboards Data-driven Publishing Cost-Benefit 111

AWS Big Data

APRIL 19, 2023

Customers now want to migrate their Apache Hive workloads to Apache Spark in the cloud to get the benefits of optimized runtime, cost reduction through transient clusters, better scalability by decoupling the storage and compute, and flexibility. Generate Spark SQL metadata Our batch job consists of Hive steps scheduled to run sequentially.

Metadata 77

Metadata Testing Data Lake Consulting 77

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 100

Metadata Data Lake Publishing Data Governance 100

AWS Big Data

NOVEMBER 15, 2023

You can use its built-in transformations, recipes, as well as integrations with the AWS Glue Data Catalog and Amazon Simple Storage Service (Amazon S3) to preprocess the data in your landing zone, clean it up, and send it downstream for analytical processing. For Matching conditions , choose Match all conditions.

Metadata 83

Metadata Sales Data Lake Big Data 83

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

JULY 14, 2023

The FinAuto team built AWS Cloud Development Kit (AWS CDK), AWS CloudFormation , and API tools to maintain a metadata store that ingests from domain owner catalogs into the global catalog. This global catalog captures new or updated partitions from the data producer AWS Glue Data Catalogs.

Finance 80

Finance Metadata Big Data Recreation/Entertainment 80

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 56

Analytics Data Lake Testing Optimization 56

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. Nominations for the 2021 Cloudera Data Impact Awards are open from now until July 23.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 80

Data Lake Dashboards Metrics Metadata 80

AWS Big Data

FEBRUARY 21, 2023

We dive deep into a hybrid approach that aims to circumvent the issues posed by these two and also provide recommendations to take advantage of this approach for healthcare data warehouses using Amazon Redshift. What is a dimensional data model? It optimizes the database for faster data retrieval. What is a data vault?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

JANUARY 22, 2024

Data as a product Treating data as a product entails three key components: the data itself, the metadata, and the associated code and infrastructure. In this approach, teams responsible for generating data are referred to as producers. Srikant Das is an Acceleration Lab Solutions Architect at Amazon Web Services.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

Andrew White

OCTOBER 22, 2021

Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Portfolio Planning/Optimization 5. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Metadata Strategy 3. Business Innovation with D&A 6.

IT 52

IT Data Lake Strategy Data Science 52

Andrew White

JANUARY 11, 2021

Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Data lakes don’t offer this nor should they. Governance. Product Management.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. For more information about checkpointing, see the appendix at the end of this post. Subramanya Vajiraya is a Sr.

Management 76

Management Metadata Testing Internet of Things 76

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

MARCH 21, 2023

As an industry with tight margins, travel and tourism companies can use analytics to detect trends that help them reduce costs, decide future product and service offerings, and develop successful business strategies. Why is data analytics important for travel organizations? How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

IBM Big Data Hub

OCTOBER 4, 2023

Another IDC study showed that while 2/3 of respondents reported using AI-driven data analytics, most reported that less than half of the data under management is available for this type of analytics. from 2022 to 2026. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 86

Data Lake Metadata Cost-Benefit Data Warehouse 86

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 117

Data Lake Unstructured Data Data Warehouse Data Quality 117

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 84

Cost-Benefit Metadata Data Governance Modeling 84

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape.

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Metadata in cluster is disjoint across components.

Data Lake 99

Data Lake Cost-Benefit Testing Metadata 99

Cloudera

DECEMBER 16, 2022

We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP). Cloudera has always been in the forefront of disruptive technical innovation in data platforms. 2-A truly open data lakehouse.

Management 90

Management Metadata Machine Learning Data Lake 90

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

MAY 9, 2023

A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. Optimized for all data, analytics and AI workloads, watsonx.data combines the flexibility of a data lake with the performance of a data warehouse, helping businesses to scale data analytics and AI anywhere their data resides.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics.

Data Governance 84

Data Governance Metadata Data-driven Enterprise 84