Cloudera

SEPTEMBER 29, 2022

Data Mesh is a concept used to help scale a company’s data footprint in a manageable way. It is a set of rubrics around people, process, and technology choices that allow for companies to scale their data systems. . Data mesh conceptual hierarchy. The data itself is then treated as a product. Miro: [link].

Data Architecture 73

Data Architecture Metadata Data Warehouse Sales 73

erwin

APRIL 2, 2021

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Do You Know Where Your Sensitive Data Is? erwin Data Intelligence.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Cloudera

NOVEMBER 12, 2020

In addition, costs generated by independent IT projects frequently skyrockets with few controls in place to manage them. At Cloudera, we listened to our customers’ problems and built the Burst to Cloud feature in Workload Manager (WXM), Cloudera’s intelligent workload management tool. A solution.

Data Warehouse 102

Data Warehouse Reporting Risk Cost-Benefit 102

Octopai

NOVEMBER 24, 2021

As the first of its reasons why to migrate to Redshift , Amazon says, “Amazon Redshift is fully managed and simple to use, enabling you to deploy a new data warehouse in minutes and load virtually any type of data from a range of cloud or on-premises data sources.”. Setting up the data warehouse can take minutes.

Data Warehouse 73

Data Warehouse Metadata Data Processing Reporting 73

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. 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. The data can be reattached to UltraWarm when needed.

Data Lake 116

Data Lake Analytics Dashboards Metrics 116

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 77

Metadata Data Lake Data Processing Data-driven 77

Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. SECURITY AND GOVERNANCE LEADERSHIP.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Granted, I’m no expert in DG.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 105

Management Advertising Data Lake Sales 105

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 144

Management Advertising Data Lake Sales 144

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Later, BI tools such as Chartio, Looker, and Tableau arrived on the data scene.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

MARCH 26, 2024

AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud. Streaming data with low latency needs is stored in Amazon Kinesis Data Streams for real-time consumption.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. You already know that a distributed environment is much tougher for your company to manage, secure, and govern. Yes there is a better choice!

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

AWS Big Data

MARCH 9, 2023

Thousands of customers rely on Amazon Redshift to build data warehouses to accelerate time to insights with fast, simple, and secure analytics at scale and analyze data from terabytes to petabytes by running complex analytical queries. Data loading is one of the key aspects of maintaining a data warehouse.

Slice and Dice 82

Slice and Dice Data Warehouse Metrics Metadata 82

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. InstanceId[]' Go to the Amazon EC2 console and connect to the master node through the Session Manager. or later installed. Instances[].InstanceId[]'

Big Data 82

Big Data Data Processing Interactive Testing 82

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Clearly, SQL helps reduce cognitive load for those who are learning about data management and analytics.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

IBM Big Data Hub

JULY 17, 2023

Additional capabilities of our ML and data science toolkit include: MLOps pipelines: Offers a collaborative studio for data scientists to build, train and deploy machine learning models with advanced features like automated machine learning and model monitoring. Later this year, it will leverage watsonx.ai

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

Alation

FEBRUARY 8, 2022

While data fabric takes a product-and-tech-centric approach, data mesh takes a completely different perspective. Data mesh inverts the common model of having a centralized team (such as a data engineering team), who manage and transform data for wider consumption. Principle #2: Data as a product.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

Cloudera

NOVEMBER 13, 2017

The net result is much improved productivity for data engineers, data scientists, and analysts. Unified – Conceptually, cloud sounds like a single place to host diverse, data-intensive functions. The ability to discover and define metadata definitions for the business is a critical enabler for self-service functions.

Analytics 40

Analytics Big Data Machine Learning Cost-Benefit 40

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

Laminar Security

MAY 3, 2023

So while the cloud has become an integral part of doing business, data security in the cloud is lagging behind. They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms.

Management 52

Management Risk Risk Management Data Processing 52

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 92

Data Lake Data Warehouse Data-driven B2B 92

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

Cloudera

MAY 18, 2021

Second, since IaaS deployments replicated the on-premises HDFS storage model, they resulted in the same data replication overhead in the cloud (typical 3x), something that could have mostly been avoided by leveraging modern object store. moving HDFS data to S3 using DistCp for basic data backups) for data lifecycle management capabilities.

Cost-Benefit 84

Cost-Benefit Data-driven Data Warehouse Machine Learning 84

Andrew White

JANUARY 11, 2021

On January 4th I had the pleasure of hosting a webinar. It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. How do you think Technology Business Management plays into this strategy? Product Management.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

Now, Delta managers can get a full understanding of their data for compliance purposes. Additionally, with write-back capabilities, they can clear discrepancies and input data. This also includes IT departments that develop and manage applications used by internal stakeholders and partners.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52