Precisely

AUGUST 3, 2023

For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their data programs. Half of the respondents (50%) say their strategies are influenced by advanced data analytics, a critical technology for amplifying data-driven decision-making. One major finding?

DataOps 98

DataOps Data Quality Analytics Analytics 98

Alation

JUNE 21, 2022

ML and DataOps teams). Power business users and other non-purely-analytic data citizens came after that. analysts, data scientists, compliance, stewards, data engineers, analytics engineers ) executing multiple use cases (e.g., At one level, it makes sense – there is certainly a lot of interest in DataOps today.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Data Science 101

APRIL 12, 2019

The company develops a DataOps platform that can allow business to manage streaming data flows. 1010 Data has its headquarter in the New York and the company has over 15 years of experience in handling data analytics with over 850 clients across various industries. This company is great for business analytics. 2 StreamSets.

Data Scientist 110

Data Scientist Data Science DataOps Hadoop 110

IBM Journey to AI blog

OCTOBER 22, 2024

Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics. This process is known as data integration , one of the key components to improving the usability of data for AI and other use cases, such as business intelligence (BI) and analytics.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Precisely

FEBRUARY 10, 2023

Advanced analytics and AI/ML continue to be hot data trends in 2023. DataOps Delivers Continuous Improvement and Value In IDC’s spotlight report, Improving Data Integrity and Trust through Transparency and Enrichment , Research Director Stewart Bond highlights the advent of DataOps as a distinct discipline.

DataOps 52

DataOps Data Observability ML ML 52

IBM Journey to AI blog

AUGUST 12, 2024

Whereas AIOps is a comprehensive discipline that includes a variety of analytics and AI initiatives that are aimed at optimizing IT operations, MLOps is specifically concerned with the operational aspects of ML models, promoting efficient deployment, monitoring and maintenance.

Big Data 106

Big Data Big Data ML ML 106

Alation

JANUARY 25, 2022

A data fabric utilizes continuous analytics over existing, discoverable, and inferred metadata assets to support the design, deployment, and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms.” Automated Data Orchestration (AKA DataOps). ” 1. Spoiler alert!

DataOps 52

DataOps SQL ML ML 52

Precisely

JULY 15, 2024

Key Takeaways Data Mesh is a modern data management architectural strategy that decentralizes development of trusted data products to support real-time business decisions and analytics. DataOps tools and strategies help discrete domains share repeatable workflows, reducing the duplication of efforts and improving efficiency.

Data Governance 72

Data Governance DataOps Data Silos Data Pipeline 72

Precisely

FEBRUARY 9, 2024

Data Integrity Supports Continued Modernization Momentum Organizations are adopting cloud services for more cost-effective, agile, and scalable data analytics, artificial intelligence, and the development of new applications. That approach assumes that good data quality will be self-sustaining.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Iguazio

JANUARY 16, 2024

This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. The AI/Ml team is made up of ML engineers, data scientists and backend product engineers.

ML 52

ML ML DataOps Data Scientist 52

Iguazio

JANUARY 16, 2024

This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. The AI/Ml team is made up of ML engineers, data scientists and backend product engineers.

ML 52

ML ML DataOps Data Scientist 52

IBM Journey to AI blog

SEPTEMBER 5, 2024

Value realization Good data governance aims to maximize the value of data as a strategic asset, enhancing decision-making, big data analytics , machine learning and artificial intelligence projects. DevOps and DataOps are practices that emphasize developing a collaborative culture.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

Precisely

SEPTEMBER 18, 2023

Regardless of your industry or role in the business, data has a massive role to play – from operations managers who rely on downstream analytics for important business decisions, to executives who want an overview of how the company is performing for key stakeholders. Data observability is a key element of data operations (DataOps).

Data Observability 52

Data Observability Data Quality Data Pipeline DataOps 52

Precisely

JUNE 26, 2023

Forward-thinking businesses invest in digital transformation, cloud adoption, advanced analytics and predictive modeling, and supply chain resiliency. 2023 Data Integrity Trends & Insights Results from a Survey of Data and Analytics Professionals Read the report Here are some of the top takeaways that stood out to panelists.

Data Quality 52

Data Quality Data Silos Analytics Data Governance 52

Alation

SEPTEMBER 14, 2021

This is regardless of whether your goal is selling the value of analytics or responding to governmental regulation. Given this, data governance should be a key enabler of DataOps. It improves governance processes and makes DataOps processes less constraining upon organizations. Data governance is not a “one and done.”

Data Governance 52

Data Governance DataOps Machine Learning Machine Learning 52

Iguazio

JULY 22, 2024

MongoDB for end-to-end AI data management MongoDB Atlas , an integrated suite of data services centered around a multi-cloud NoSQL database, enables developers to unify operational, analytical, and AI data services to streamline building AI-enriched applications.

AI 132

AI AI ML ML 132

ODSC - Open Data Science

JULY 20, 2023

Learn how to eliminate data downtime and ensure data trust at scale with end-to-end data observability, a critical component of the modern DataOps workflow. Join this webinar to learn how to easily generate insights from unstructured data by customizing an LLM with open-source declarative ML framework, Ludwig, and Predibase.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Alation

APRIL 4, 2023

Alation delivers extended connectivity for Databricks Unity Catalog , the lakehouse company, and new connectivity for dbt Cloud by dbt Labs , the pioneer in analytics engineering. With the launch of our latest product release, 2023.1, At the heart of this release is the need to empower people with the right information at the right time.

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52

AWS Machine Learning Blog

APRIL 17, 2023

The transformations in the Data Wrangler flow can now be scaled in to a pipeline for DataOps. He has extensive experience in end-to-end designs and solutions for machine learning; business analytics within financial, operational, and marketing analytics; healthcare; supply chain; and IoT.

AWS 99

AWS ML ML Python 99

phData

OCTOBER 8, 2024

Throughout our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps. Analytics Engineering: Our experienced analytics engineers employ dbt models to pull out new business insights and automate existing reports.

DataOps 52

DataOps Data Modeling Data Models SQL 52

phData

MAY 11, 2023

With the “Data Productivity Cloud” launch, Matillion has achieved a balance of simplifying source control, collaboration, and dataops by elevating Git integration to a “first-class citizen” within the framework. An analytics program’s maturity curve is not navigated by all members at the same rate. When Is ZDLC Better Than SDLC?

ETL 52

ETL Analytics Analytics Data Modeling 52

Precisely

DECEMBER 12, 2023

Data observability is a foundational element of data operations (DataOps). It ensures the reliability of your processes and analytics by alerting you to potentially problematic events as soon as they occur. In either case, the change can affect analytics. The application of this concept to data is relatively new.

Data Observability 52

Data Observability Data Quality Data Pipeline Machine Learning 52

Dataversity

JULY 1, 2022

From payments to CRM to analytics and people operations, software runs everything. A 20-year-old article from MIT Technology Review tells us that good software “is usable, reliable, defect-free, cost-effective, and maintainable. And software now is none of those things.” Today, most businesses would beg to differ.

Analytics 52

Analytics Analytics DataOps Data Pipeline 52

phData

OCTOBER 16, 2023

Throughout our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps. Analytics Engineering: Our experienced analytics engineers employ dbt models to pull out new business insights and automate existing reports.

DataOps 52

DataOps Data Modeling Data Models SQL 52

phData

JUNE 26, 2023

Through our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps.

DataOps 52

DataOps Hadoop Analytics Analytics 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. A modern data stack is basically a combination of these new products that have come together to help deliver analytics. Tools became stacks. Why are they so popular?

Data Warehouse 52

Data Warehouse Data Engineering Data Engineer Data Engineering 52

Alation

MAY 24, 2022

Data quality is one of the primary signals behind whether or not a data asset or analytical report can be trusted. So understanding data quality is extremely important for an organization to drive the correct decisions from analytics. Data consumers need that information to trust that the data is good to use.

Data Quality 52

Data Quality Data Pipeline DataOps Analytics 52

AWS Machine Learning Blog

JULY 31, 2023

He works with customers to realize their data analytics and machine learning goals through adoption of DataOps and MLOps practices and solutions. He designs modern application architectures based on microservices, serverless, APIs, and event-driven patterns.

ML 95

ML ML Data Preparation Machine Learning 95

Alation

APRIL 18, 2023

This ability improves the accuracy of analytics, resulting in better business decisions. “Current profiling tools are point and click, which free up my time for analysis. It’s a huge time saver, and it gives you so much information. You can focus on other things instead of writing the code.”

Data Profiling 52

Data Profiling Data Quality Data Governance Data Pipeline 52

Pickl AI

DECEMBER 11, 2024

AI-driven tools also facilitate predictive analytics, enabling businesses to make proactive decisions. Leverage governance frameworks like DataOps to align data management practices with regulatory requirements such as GDPR or CCPA. Companies can allocate their human resources to more strategic tasks by automating these processes.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

Dataversity

JUNE 23, 2021

Click to learn more about author Jitesh Ghai. The role of the chief data officer (CDO) has evolved more over the last decade than any of the C-suite. A position once laser-focused on regulatory compliance is today one of the most strategic enterprise decision-makers. As companies plan for a rebound from the pandemic, the CDO […].

AI 59

AI AI DataOps Data Quality 59

Dataversity

FEBRUARY 4, 2021

Click to learn more about author Keith D. Currently, many businesses are using public clouds to do their Data Management. Data Management platforms (DMPs) started becoming popular during the late 1990s and the early 2000s.

Data Observability 59

Data Observability DataOps Cloud Data Analytics 59

The Data Administration Newsletter

FEBRUARY 15, 2022

The future of data democratization lies in the hands of your end-users. They are already generating data, they know what problems they need to solve with it, and they know how to use that information for business value. It is time you let the end-users pull their own weight without having to rely on IT […].

DataOps 52

DataOps Big Data Big Data Business Intelligence 52