AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

CIO Business Intelligence

APRIL 25, 2024

For instance, a Data Cloud-triggered flow could update an account manager in Slack when shipments in an external data lake are marked as delayed. Sharing Customer 360 insights back without data replication. Currently, Data Cloud leverages live SQL queries to access data from external data platforms via zero copy.

Data Integration 59

Data Integration Data Lake Metadata Data Warehouse 59

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

Data Lake 90

Data Lake Cost-Benefit Visualization Structured Data 90

CIO Business Intelligence

MARCH 29, 2024

Modernizing data operations CIOs like Woodring know well that the quality of an AI model depends in large part on the quality of the data involved — and how that data is injected from databases, data warehouses, cloud data lakes, and the like into large language models.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 81

Data Lake Big Data Consulting Data Warehouse 81

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

FEBRUARY 7, 2023

Business needs often drive table structure, such as schema evolution (the addition of new columns, removal of existing columns, update of column names, and so on) for some of these tables in one business function that requires other business functions to replicate the same. You don’t alter queries separately in the data lake.

Data Lake 70

Data Lake Testing Big Data Structured Data 70

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. CDP Data Lake cluster versions – CM 7.4.0,

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

AWS Big Data

MARCH 25, 2024

Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

Data Lake 87

Data Lake Unstructured Data Management Modeling 87

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 98

Statistics Data Lake Optimization Data-driven 98

CIO Business Intelligence

APRIL 26, 2024

Following its acquisition of Neustar, a Google Cloud Platform customer, TransUnion embraced a multicloud infrastructure that also supports GCP, but the crown jewel of its technology modernization is OneTru, and its 50 petabytes of data assets amassed over decades.

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IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

Management 87

Management IT Machine Learning Metrics 87

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

CIO Business Intelligence

DECEMBER 4, 2023

A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data. When data is stored in a modern, accessible repository, organizations gain newfound capabilities.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. 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. It consists of full-day and intraday tables.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 68

Data Lake Testing Snapshot Sales 68

CIO Business Intelligence

OCTOBER 25, 2023

The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data. Once shared, this data can be fed into the data lakes used to train large language models (LLMs) and can be discovered by other users.

Enterprise 133

Enterprise Risk Manufacturing Finance 133

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

IBM Big Data Hub

JULY 5, 2022

Vektis improves healthcare quality through data . Store and query more than just traditional structured data with multi-model capabilities. Seamlessly integrate Db2 with your existing data lake to easily query datasets residing in open data formats like Parquet, Avro and more.

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

IBM Big Data Hub

APRIL 25, 2023

Similarly, the relational database has been the foundation for data warehousing for as long as data warehousing has been around. Relational databases were adapted to accommodate the demands of new workloads, such as the data engineering tasks associated with structured and semi-structured data, and for building machine learning models.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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

AWS Big Data

NOVEMBER 9, 2023

This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake. You can also use features like auto-copy from Amazon S3 (feature under preview) to ingest data from Amazon S3 to Amazon Redshift.

Data Warehouse 101

Data Warehouse Testing Data Quality Reporting 101

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Lake 74

Data Lake Data Warehouse Sales Data-driven 74

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed, cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you to securely access your data in operational databases, data lakes or third-party datasets with minimal movement or copying.

Data Warehouse 79

Data Warehouse Data-driven Testing Business Intelligence 79

Alation

FEBRUARY 20, 2020

By changing the cost structure of collecting data, it increased the volume of data stored in every organization. Additionally, Hadoop removed the requirement to model or structure data when writing to a physical store. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 79

Big Data Software Consulting Unstructured Data 79

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

Octopai

MAY 30, 2019

The Benefits of Structured Data Catalogs. 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. They have little in the way of definition or categorization.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 27, 2024

Amazon Redshift integrates with AWS HealthLake and data lakes through Redshift Spectrum and Amazon S3 auto-copy features, enabling you to query data directly from files on Amazon S3. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 88

Data Analytics Analytics Data Warehouse Data Lake 88

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices.

IoT 56

IoT Internet of Things Big Data Data-driven 56