DataKitchen

AUGUST 3, 2021

Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. It’s no fun working in data analytics/science when you are the bottleneck in your company’s business processes. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

AUGUST 11, 2023

In today’s digital world, the ability to make data-driven decisions and develop strategies that are based on data analytics is critical to success in every industry. The IDH will be a game-changing platform that allows us to make data available to data scientists and data analysts across the company.

Data Analytics 98

Data Analytics Analytics Data-driven Business Driver 98

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. Automated workflows for data product creation, testing and deployment.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

AWS Big Data

DECEMBER 4, 2024

It’s the preferred choice when customers need more control and customization over the data integration process or require complex transformations. This flexibility makes Glue ETL suitable for scenarios where data must be transformed or enriched before analysis. Kamen Sharlandjiev is a Sr.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

AWS Big Data

DECEMBER 13, 2023

The AWS Glue Studio visual editor is a low-code environment that allows you to compose data transformation workflows, seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine, and inspect the schema and data results in each step of the job.

Metadata 111

Metadata Data Lake Visualization Data Quality 111

AWS Big Data

FEBRUARY 29, 2024

Implement data privacy policies. Implement data quality by data type and source. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail. Link structured and unstructured datasets.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

CIO Business Intelligence

SEPTEMBER 11, 2024

But here’s the real rub: Most organizations’ data stewardship practices are stuck in the pre-AI era, using outdated practices, processes, and tools that can’t meet the challenge of modern use cases. Data stewardship makes AI your superpower In the AI era, data stewards are no longer just the data quality guardians.

Data Quality 118

Data Quality Unstructured Data Metadata Data Governance 118

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. Monitoring Job Metadata.

Testing 154

Testing Metadata Dashboards Statistics 154

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

CIO Business Intelligence

NOVEMBER 22, 2022

“Unique insights derived from an organization’s data constitute a competitive advantage that’s inherent to their business and not easily copied by competitors,” she observes. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Smart Data Collective

SEPTEMBER 26, 2021

The best part about data workflow management is that you can take a task and develop a custom solution to bring clarity to the entire team on what needs to be done and, most importantly, how. It’s a good idea to record metadata. The metadata describes exactly how observations were collected, formatted, and organized.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

Cloudera

MARCH 3, 2022

In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. The medical insurance company wasn’t hacked, but its customers’ data was compromised through a third-party vendor’s employee. 86% of Experian survey respondents’, for instance, are prioritizing moving their data to the cloud in 2022.

Data Governance 100

Data Governance Enterprise Data Quality Metadata 100

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 363

Management Machine Learning Experimentation Metrics 363

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing. For Matching conditions , choose Match all conditions.

Metadata 114

Metadata Sales Data Lake Big Data 114

erwin

FEBRUARY 4, 2021

As we zeroed in on the bottlenecks of day-to-day operations, 25 percent of respondents said length of project/delivery time was the most significant challenge, followed by data quality/accuracy is next at 24 percent, time to value at 16 percent, and reliance on developer and other technical resources at 13 percent.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. As the first and most impactful of all benefits of analytics, we have the ability to make informed strategic decisions backed by factual information.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Alation

MAY 19, 2022

Establish what data you have. Active metadata gives you crucial context around what data you have and how to use it wisely. Active metadata provides the who, what, where, and when of a given asset, showing you where it flows through your pipeline, how that data is used, and who uses it most often.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

AWS Big Data

MAY 1, 2024

Excel-based data utilization Microsoft Excel is available on almost everyone’s PC in the company, and it helps lower the hurdles when starting to utilize data. However, Excel is mainly designed for spreadsheets; it’s not designed for large-scale data analytics and automation.

Dashboards 124

Dashboards Publishing Data-driven Cost-Benefit 124

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? As you can tell, data governance is a hot topic but an area that many public cloud vendors are weak in. The post Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? So, why did I decide to write on this topic? I am glad you asked.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 79

Management Metadata Data Architecture Data Lake 79

Alation

OCTOBER 5, 2021

However, about 50% of those surveyed also admit that they do not assess, monitor, or measure their data governance systems. Perhaps even more alarming: fewer than 33% expect to exceed their returns on investment for data analytics within the next two years. Data governance and AI.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. Security: It must serve data throughout a system.

Data Governance 86

Data Governance Metadata Data-driven Enterprise 86

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. Airflow will cache variables and connections locally so that they can be accessed faster during DAG parsing, without having to fetch them from the secrets backend, environments variables, or metadata database.

Metrics 122

Metrics Metadata Snapshot Management 122

IBM Big Data Hub

JANUARY 17, 2023

These new technologies and approaches, along with the desire to reduce data duplication and complex ETL pipelines, have resulted in a new architectural data platform approach known as the data lakehouse – offering the flexibility of a data lake with the performance and structure of a data warehouse.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own.

Visualization 98

Visualization Reporting Metadata Enterprise 98