AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 134

Analytics IoT Data-driven Snapshot 134

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. By using features like Icebergs compaction, OTFs streamline maintenance, making it straightforward to manage object and metadata versioning at scale.

Data Lake 52

Data Lake IoT Metadata Testing 52

Cloudera

SEPTEMBER 23, 2020

Access audits are mastered centrally in Apache Ranger which provides comprehensive non-repudiable audit log for every access event to every resource with rich access event metadata such as: IP. Both fine-grained access control of database objects and access to metadata is provided. Sensitive data identification.

Data Lake 84

Data Lake Metadata IoT Enterprise 84

Data Virtualization

AUGUST 26, 2020

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

Data Architecture 59

Data Architecture Internet of Things Data Lake IoT 59

AWS Big Data

FEBRUARY 21, 2023

At the heart of all data warehousing is integration, and this layer contains integrated data from multiple sources built around the enterprise-wide business keys. Although data lakes resemble data vaults, a data vault provides more features of a data warehouse. What is a hybrid model?

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Metadata 88

AWS Big Data

DECEMBER 16, 2024

This approach simplifies your data journey and helps you meet your security requirements. The SageMaker Lakehouse data connection testing capability boosts your confidence in established connections. About the Authors Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team.

Visualization 88

Visualization Data Processing Testing Publishing 88

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric promotes data discoverability.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

MAY 12, 2021

This category is open to organizations that have tackled transformative business use cases by connecting multiple parts of the data lifecycle to enrich, report, serve, and predict. . DATA FOR ENTERPRISE AI. Industry Transformation: Telkomsel — Ingesting 25TB of data daily to provide advanced customer analytics in real-time .

Digital Transformation 72

Digital Transformation Machine Learning Optimization Data Lake 72

Octopai

MAY 30, 2019

At the most basic level, data catalogs help you organize your company’s massive datasets. Most enterprises have huge data lakes with millions of touchpoints all living in the dark. It’s not enough to simply store customer data in siloed systems; companies need to be able to locate specific metadata points when needed.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 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.

Management 98

Management Metadata Testing Internet of Things 98

Alation

APRIL 14, 2022

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. The Cloud Data Migration Challenge. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 46

Big Data Data Lake Internet of Things Enterprise 46

In(tegrate) the Clouds

DECEMBER 21, 2015

Aside from the Internet of Things, which of the following software areas will experience the most change in 2016 – big data solutions, analytics, security, customer success/experience, sales & marketing approach or something else? 2016 will be the year of the data lake.

Technology 45

Technology Internet of Things Digital Transformation Software 45

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 129

Metadata Cost-Benefit Enterprise Interactive 129

Alation

AUGUST 2, 2022

Customer centricity requires modernized data and IT infrastructures. Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics. Data discovery was conducted 67% times faster.

Cost-Benefit 52

Cost-Benefit Metrics Strategy Data Lake 52