Octopai

OCTOBER 26, 2022

Enter DataOps. How can DataOps help here? The goal of DataOps methodology is to enable Data to drive Op eration s : to have a direct, constructive impact on the business operations of the company. DataOps realizes that the purpose of having data is to use the data. So what is DataOps ? Six DataOps best practices.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Alation

SEPTEMBER 21, 2021

Modern data environments are highly distributed, diverse, and dynamic, many different data types are being managed in the cloud and on-premises, in many different data management technologies, and data is continuously flowing and changing – not unlike traffic on a highway. The Rise of Gen-D and DataOps. Data Intelligence Benefits.

Metadata 52

Metadata Testing Recreation/Entertainment Data-driven 52

IBM Big Data Hub

MAY 25, 2023

In addition, the CoE will develop new solutions and assets with clients and partners, leveraging the pipeline of generative AI innovations from IBM Research. We will also use IBM’s proprietary AI “advisor” toolkit in IBM Consulting to improve our internal operations and client delivery.

Consulting 106

Consulting Experimentation Machine Learning Modeling 106

AWS Big Data

AUGUST 11, 2023

Customers are implementing data and analytics workloads in the AWS Cloud to optimize cost. Serverless services like AWS Glue minimize the need to think about servers and focus on offering additional productivity and DataOps tooling for accelerating data pipeline development.

Data Processing 95

Data Processing Cost-Benefit Optimization Interactive 95

IBM Big Data Hub

NOVEMBER 4, 2022

We are excited to share that Gartner recently named IBM a Leader in the 2022 Gartner® Magic Quadrant for Data Quality Solutions. This complements IBM’s partnership with MANTA to integrate automated data lineage capabilities from MANTA with IBM Watson Knowledge Catalog on Cloud Pak for Data. Unlock quality data with IBM.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Ramsey International Modern Data Platform Architecture. What is a data mesh?

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

IBM Big Data Hub

APRIL 12, 2022

When I joined IBM in 2016, our business strategy centered on hybrid cloud and AI. Thus IBM, itself, served as client zero and became a showcase of our solutions in the data and AI space. In terms of implementing that strategy, we set several key pieces in place, such as: A hybrid distributed cloud and AI platform.

Data Strategy 82

Data Strategy Strategy Enterprise Data-driven 82

AWS Big Data

NOVEMBER 9, 2023

Building a data platform involves various approaches, each with its unique blend of complexities and solutions. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Let’s explore the architecture and learn how to build this use case using AWS Cloud services.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

Octopai

OCTOBER 31, 2022

This dilemma is dealt with by the emerging field of DataOps and one of its chief components: data observability. A DataOps view prescribes that the purpose of having data is to use the data. the uninterrupted smooth functioning of developed data products) requires data observability tools and solutions.

Experimentation 52

Experimentation Machine Learning Manufacturing Management 52

DataKitchen

APRIL 13, 2021

Download the 2021 DataOps Vendor Landscape here. DataOps is a hot topic in 2021. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. As a result, vendors that market DataOps capabilities have grown in pace with the popularity of the practice.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

NOVEMBER 29, 2021

DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. With data and tools increasingly in the cloud, data organizations are finding ways to accommodate remote work. DataOps is the perfect partner to data mesh. .

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

AWS Big Data

JANUARY 17, 2024

Solution overview In this post, we demonstrate how to implement FGAC on Apache Hudi tables using Amazon EMR on Amazon Elastic Compute Cloud (Amazon EC2) integrated with Lake Formation. The following diagram illustrates the solution architecture. For example, the users only can access data rows that belong to their country.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

Alation

SEPTEMBER 14, 2021

With this change, we seek to better tailor our solution to the precise needs of each customer. Specifically, it simplifies how organizations enable secure access to the best data in today’s hybrid & multi-cloud environments. Given this, data governance should be a key enabler of DataOps.

Data Governance 52

Data Governance Dashboards Measurement Machine Learning 52

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads. Oozie on HDInsight.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Alation

AUGUST 17, 2022

In many ways proper data governance can enable new uses of data, new revenue opportunities, and moving data to the cloud,” says analyst Dan Kirsch “Data governance needs to wrap around data, no matter wherever it resides. Curious to learn more about data governance solutions ? Here, the culture and program need to move together. “In

Data Governance 92

Data Governance Risk Data-driven Measurement 92

DataKitchen

MARCH 8, 2023

DataOps Observability is an essential practice in modern data-driven organizations that ensures real-time insights into the manufacturing process. DataOps Observability refers to real-time monitoring, detecting, and diagnosing of data status, data pipelines, data tools, and other systems.

Analytics 130

Analytics Manufacturing Data-driven Data Analytics 130

CIO Business Intelligence

OCTOBER 18, 2023

In September 2021, Fresenius set out to use machine learning and cloud computing to develop a model that could predict IDH 15 to 75 minutes in advance, enabling personalized care of patients with proactive intervention at the point of care. Each of those were associated with blockers, real and perceived. “It

Predictive Analytics 131

Predictive Analytics Analytics Machine Learning Digital Transformation 131

AWS Big Data

MARCH 13, 2023

AnyCompany wants to migrate this application to the AWS Cloud and use Amazon MSK to reduce maintenance and operations overhead. AnyCompany has a DataOps team that has been operating self-managed Kafka clusters in their data centers for years. The second application is a new cloud-native gaming application currently in development.

Optimization 76

Optimization Management Metrics Metadata 76

Cloudera

JULY 26, 2021

Once we have identified those capabilities, the second article explores how the Cloudera Data Platform delivers those prerequisite capabilities and has enabled organizations such as IQVIA to innovate in Healthcare with the Human Data Science Cloud. . hybrid or public, multi-cloud) and advanced analytical frameworks (e.g.,

Strategy 114

Strategy Marketing Unstructured Data Data Science 114

CIO Business Intelligence

JUNE 29, 2022

As cloud adoption has continued to rise in recent years in response to businesses’ need for agility, cost savings, innovation, and digital transformation, organizations are faced with new challenges and opportunities that impact business operations. What follows are edited excerpts of that presentation. So what does this mean?

Cost-Benefit 79

Cost-Benefit Data-driven Digital Transformation Manufacturing 79

DataRobot Blog

SEPTEMBER 13, 2022

Once an organization has identified its AI use cases , data scientists informally explore methodologies and solutions relevant to the business’s needs in the hunt for proofs of concept. Driving Innovation with AI: Getting Ahead with DataOps and MLOps. See DataRobot AI Cloud in Action. BARC ANALYST REPORT. Download Now.

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

AWS Big Data

APRIL 12, 2023

We also share a Spark benchmark solution that suits all Amazon EMR deployment options, so you can replicate the process in your environment for your own performance test cases. The solution uses the TPC-DS dataset and unmodified data schema and table relationships, but derives queries from TPC-DS to support the SparkSQL test cases.

Testing 73

Testing Big Data Metadata Optimization 73

Alation

DECEMBER 13, 2022

Today a modern catalog hosts a wide range of users (like business leaders, data scientists and engineers) and supports an even wider set of use cases (like data governance , self-service , and cloud migration ). Cloud migration. The post Data Catalog: Part of the Solution – or Part of the Problem? Data governance. Self-service.

Metadata 52

Metadata Data Governance Enterprise Insurance 52

AWS Big Data

OCTOBER 18, 2023

To look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust set of big data tools in the AWS Cloud to support these activities. Solution Overview To get started, let’s look at the following diagram. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS.

Big Data 79

Big Data Data Processing Interactive Testing 79

AWS Big Data

FEBRUARY 1, 2023

Implementation strategy Based on these requirements, we changed strategies and started analyzing each issue to identify the solution. It also includes additional productivity and DataOps tooling for authoring, running jobs, and implementing business workflows. About the authors Avinash Kolluri is a Senior Solutions Architect at AWS.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Alation

MAY 31, 2023

He also works with data engineers and business teams to help them understand the Google Cloud Platform and ensure the success of their implementations. Anil Kumar Kunden helps define, build, and monitor the company’s governance automation initiative at American Family Insurance.

Data Governance 52

Data Governance Insurance Metadata Data-driven 52

Alation

AUGUST 11, 2022

DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. And now with some of these cloud data warehouses becoming such behemoths, everything is getting centralized again. Tools became stacks. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

O'Reilly on Data

SEPTEMBER 11, 2019

The mixed signals about ML-related themes in this year’s proposals may indicate either a shift in focus of enterprise ML practices from tools and techniques to production-oriented solutions, or that we are approaching something like peak ML. The model has become a means to an end—i.e., doing something with data—rather than the end itself.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Cloudera

NOVEMBER 27, 2023

But the burden of development and maintenance of these solutions often fell on small teams of Java programmers. Cloud-only solutions will not meet the needs for many use cases and run the risk of creating additional barriers for organizations. Paimon might be a technology solution in search of a problem. Hybrid matters!

Data Lake 79

Data Lake Advertising ROI Data Warehouse 79

Cloudera

FEBRUARY 22, 2021

That benefit comes from Replication Manager , a key capability of CDP , that enables users to migrate existing, on-premises use cases to the public cloud with the same security and governance configurations. CDP Public Cloud eliminates the need for using those tools by providing the following capabilities: .

Cost-Benefit 77

Cost-Benefit Data Warehouse Data Processing Data Governance 77

Andrew White

JANUARY 11, 2021

Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. Try a little DataOps or ModelOps and see if a small, skunks-like project fan turn some folks on. What are the new trends around the Data solution architecture (centralized vs de-centralized?). Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

OCTOBER 12, 2021

DataOps. … For these reasons, self-service analytics has become a popular solution for enterprises of all industries. This solution empowers enterprises to scale both analytics and fact-based reporting with timely access to data. Spotlight friction areas and bottlenecks for data consumers (and build a solution).

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Jet Global

JULY 27, 2022

As Business Intelligence (BI) tools, data warehousing solutions, and enterprise data and application landscapes have advanced, it’s worth taking the time to rethink that old model, starting with the dichotomy between operational reporting (OR) and strategic analytics. Discover which solutions are best suited for your needs.

Operational Reporting 52

Operational Reporting Reporting Analytics Dashboards 52