Jet Global

NOVEMBER 5, 2020

Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Azure Data Lakes are highly complex and designed with a different fundamental purpose in mind than financial and operational reporting. Data lakes are not a mature technology.

Data Lake

AWS Big Data

JUNE 20, 2023

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. Data labeling is required for various use cases, including forecasting, computer vision, natural language processing, and speech recognition.

Data Lake

Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments.

Analytics

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot

Timo Elliott

NOVEMBER 21, 2022

For the last 30 years, whenever you want to do analytics, the first step is to rip it out of the operational applications and try and move it to a different environment—so data warehousing, data lakes, data lakehouses and now data clouds.

Data Analytics

Timo Elliott

MAY 27, 2022

For the longest time, in order to do any analytics, we had to take the data to the technology — rip it out of the business applications and move it to a data warehouse or a data lake, or a data lakehouse. But now, thanks to the cloud and in-memory, we can bring the technology to the data.

Data Analytics

CIO Business Intelligence

MAY 21, 2024

Real-Time Intelligence, on the other hand, takes that further by supporting data in AWS, Google Cloud Platform, Kafka installations, and on-prem installations. “We We introduced the Real-Time Hub,” says Arun Ulagaratchagan, CVP, Azure Data at Microsoft. You can monitor and act on the data and you can set thresholds.”

Broadcasting

Timo Elliott

DECEMBER 14, 2022

Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation.

Data Lake

CIO Business Intelligence

APRIL 26, 2022

Despite nearly $1 billion in online revenue in 2020, the web-based outdoor recreational retailer was running its entire business on an outdated and unsupported e-commerce platform called ADT. Backcountry also lacked many core services critical for an online retailer — no CMS, no analytics, no data platform, and no data lake.

Data Lake

Timo Elliott

JUNE 19, 2023

The next area is data. There’s a huge disruption around data. For a long time, we’ve always ripped data out of our core systems and put it into a data warehouse or a data lake or a data lake house or a data cloud. And then you have to recreate it all in this new area.

Data Lake

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake

Jen Stirrup

MAY 5, 2020

Azure allows you to protect your enterprise data assets, using Azure Active Directory and setting up your virtual network. Other technologies, such as Azure Data Factory, can help process large amounts of data around in the cloud. The data is also distributed. So, Azure Databricks connects to many different data sources.

Machine Learning

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. When your IT admin registers an environment in CDP, a Data Lake is automatically deployed. Separate compute.

Data Warehouse

Domino Data Lab

JANUARY 11, 2021

With SQLAlchemy we must specify that we wish to either append results (as in write more results to the bottom of the file) or overwrite results (as in drop the table and recreate). data = pd.read_csv('/mnt/data/modelOut.csv') data.to_sql('modelOutput', engine, index = False, if_exists='append'). About Domino Data Lab.

Data Science

Jet Global

MAY 27, 2022

How Synapse works with Data Lakes and Warehouses. Synapse services, data lakes, and data warehouses are often discussed together. Here’s how they correlate: Data lake: An information repository that can be stored in a variety of different ways, typically in a raw format like SQL.

Data Lake

CIO Business Intelligence

MARCH 20, 2023

Its acquisition of Topgolf International, completed in March 2021, added technology and tech-enabled entertainment to the mix, pushing the company toward digital transformation. Replatforming, data mining, building our data lakes to just clean the data, because back in those days it was so many systems, the data was not consistent.

Digital Transformation

Timo Elliott

NOVEMBER 30, 2022

Because of technology limitations, we have always had to start by ripping information from the business systems and moving it to a different platform—a data warehouse, data lake, data lakehouse, data cloud. It’s possible to do, but it takes huge amounts of time and effort to recreate all that from scratch.

Recreation/Entertainment

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

AWS Big Data

MAY 16, 2023

Apache Hudi provides a table format for data lakes with transactional semantics that enables the separation of ingestion workloads and updates when run concurrently. Overall, our approach to optimizing for low-latency reads with Apache Hudi allowed us to better manage file sizes and improve the overall performance of our data lake.

Data Lake

AWS Big Data

NOVEMBER 8, 2023

With real-time streaming data, organizations can reimagine what’s possible. From enabling predictive maintenance in manufacturing to delivering hyper-personalized content in the media and entertainment industry, and from real-time fraud detection in finance to precision agriculture in farming, the potential applications are vast.

Data-driven

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. You can download the dataset or recreate it locally using the Python script provided in the repository.

Data Quality

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata

Alation

JUNE 14, 2021

With effective collaboration, each contributor works toward a common goal: building off of the work of others and opening the door for more complete data governance. Without collaboration, the work of stewards is siloed and needlessly recreated. Guided Navigation Guided navigation helps data stewards locate sensitive data.

Data Governance

Andrew White

OCTOBER 24, 2019

Vision/Data Driven/Outcomes 28. Modern) Master Data Management 16. Data lake 4. Data Literacy 4. Data Management platform 7. Entertainment 1. AI/Innovation 3. AI/Automation 6. Rolls and Skills 5. Getting Started 6. D&A Strategy 19. Entity resolution/DQ 3. Emerging D&A Governance Platform 1.

Recreation/Entertainment

Cloudera

MARCH 23, 2022

Let’s say new data sources are identified for your project, and as a result new attributes need to be introduced into your existing data model. Historically this could lead to long development cycles of recreating and reloading tables, especially if new partitions are introduced.

Metadata

AWS Big Data

JULY 14, 2023

When a consumer requests table access from the central data catalog, the producer grants Lake Formation permissions to the consumer account AWS Identity and Access Management (IAM) role and tables are visible in the consumer account. The global catalog The basic building block of our business-focused solutions are data products.

Finance

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning

Cloudera

NOVEMBER 12, 2020

Inability to maintain context – This is the worst of them all because every time a data set or workload is re-used, you must recreate its context including security, metadata, and governance. Cloud deployments add tremendous overhead because you must reimplement security measures and then manage, audit, and control them.

Data Warehouse

BizAcuity

APRIL 14, 2022

The best way to avoid poor data quality is having a strict data governance system in place. The majority of the data a business has stored is generally unstructured. Most of these are accumulated in data silos or data lakes. Which means queries for large data sets might take days or eventually fail.

Big Data

Birst BI

OCTOBER 24, 2019

When we look at tools like Microsoft’s Power BI and Tableau, you must recreate complex data objects repeatedly across different teams and use cases. This is not conducive to ongoing and repeatable insights and value generation out of your data assets. This includes ETL processes and subsequent augmented and extended data sets.

Data Warehouse

Andrew White

OCTOBER 25, 2019

Vision/Data Driven/Outcomes 28. Data, analytics, or D&A Strategy 21. Modern) Master Data Management 18. Data lake 4. Data Literacy 4. IoT/Streaming data 1. Platform questions: Data Management platform 15. Media & Entertainment 3. Organization, Rolls and Skills 8. AI/Automation 6.

Recreation/Entertainment

AWS Big Data

JUNE 27, 2024

Identify the Redshift data shares that were previously configured for the original producer cluster. Recreate these data shares on the new producer cluster in the target Region. Update the data share configurations in the consumer cluster to point to the newly created producer cluster.

Snapshot

CIO Business Intelligence

JUNE 7, 2023

Like the NFL, the NBA CTO opted to partner with Microsoft to leverage its Azure cloud platform, which Bhagavathula says contained all the digital components necessary to build the association’s streaming platform, while providing a cloud data lake and machine learning models the NBA could capitalize on for next-generation applications.

Digital Transformation

AWS Big Data

JUNE 3, 2025

Plus, you can use other Amazon Redshift capabilities such as built-in machine learning, materialized views, data sharing, and federated access to multiple data stores and data lakes. You can see more other zero-ETL integrations use cases at What is ETL. Julia Beck is an Analytics Specialist Solutions Architect at AWS.

Optimization