DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance. I ended up writing two documents on data governance. To address client questions about cloud, I wrote a document on GCP.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

datapine

NOVEMBER 27, 2019

Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. local/bin/dbt test –-select your_package.* /usr/local/airflow/.local/bin/dbt

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

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

Smart Data Collective

SEPTEMBER 26, 2021

A NoSQl database can use documents for the storage and retrieval of data. The central concept is the idea of a document. Documents encompass and encode data (or information) in a standard format. A document is susceptible to change. The documents can be in PDF format. Speaking of which.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

CIO Business Intelligence

JANUARY 23, 2024

Quality metrics can be used to measure the improvements that come from reducing defects, lowering the impacts of human errors, improving data quality, and other program outcomes that illustrate how increasing quality connects to business impact. As a result, outcome-based metrics should be your guide.

Measurement 129

Measurement Digital Transformation KPI Metrics 129

erwin

FEBRUARY 4, 2021

It uncovered a number of obstacles that organizations have to overcome to improve their data operations. 1 bottleneck, according to 62 percent of respondents, was documenting complete data lineage. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. Now, with Data Dan, you only get to ask him three questions.

IT 317

IT Statistics KPI Data-driven 317

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. Top Five: Benefits of An Automation Framework for Data Governance.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

InsightOut

MAY 20, 2022

In listening to them describe their experience – what went well and not so well – and reviewing their existing approach and documentation, I have observed a number of patterns. With these projects, there are clear technical challenges that can also lead to problems, such as data quality and accessibility.

Analytics 52

Analytics Dashboards Optimization Technology 52

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. Picking the Right Data Governance Tools.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

datapine

JANUARY 21, 2020

Another crucial factor to consider is the possibility to utilize real-time data. The customizable nature of modern data analytic stools means that it’s possible to create dashboards that suit your exact needs, goals, and preferences, improving the senior decision-making process significantly. Enhanced data quality.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

Smarten

FEBRUARY 13, 2022

The world-renowned technology research firm, Gartner, predicts that, ‘through 2024, 50% of organizations will adopt modern data quality solutions to better support their digital business initiatives’. As businesses consider the options for data analytics, it is important to understand the impact of solution selection.

Analytics 52

Analytics Key Performance Indicator Business Intelligence ROI 52

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. On the flip side, document everything that isn’t working. Clean data in, clean analytics out.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

DataKitchen

FEBRUARY 21, 2023

Productivity does not come through the fingers of each data engineer; it comes from building a system around those engineers that allows them to run production with minimal errors and move things into production quickly, with low risk, so they can focus on making their customers successful. Summary: 10x your data engineering game.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

Alation

AUGUST 4, 2022

Many CIOs argue the rise of big data pushed people to use data more proactively for business decision-making. Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick. Solving this isn’t just about scale.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation. For a complete list of installed packages and their versions, refer to this MWAA documentation.

Metrics 105

Metrics Metadata Snapshot Management 105

IBM Big Data Hub

OCTOBER 12, 2023

Stored data is predicted to see a 250% growth by 2025, 1 the results of which are likely to include a greater number of disconnected silos and higher associated costs. To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

Cloudera

AUGUST 26, 2020

The Cloudera Connect Technology Certification program uses a well-documented process to test and certify our Independent Software Vendors’ (ISVs) integrations with our data platform. Certified BI Analytical Partners. Pepperdata provides observability and continuous tuning for the big data analytics stack.

Machine Learning 82

Machine Learning Big Data Data Warehouse Data-driven 82

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Reference data management.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

CIO Business Intelligence

MARCH 7, 2024

Documenting these plans and use cases will be critical to minimize the future workload if regulators come knocking (and they will). I also know that companies must have great data quality or scrubbed data to feed the AI models, or your outputs will be worthless.

Digital Transformation 70

Digital Transformation Machine Learning Risk Testing 70

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.

Metadata 86

Metadata Sales Data Lake Big Data 86

Alation

OCTOBER 12, 2021

Enterprise data analytics enables businesses to answer questions like these. Having a data analytics strategy is a key to delivering answers to these questions and enabling data to drive the success of your business. What is Enterprise Data Analytics? The third challenge was around trusting the data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Metadata 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 85

Data Governance Metadata Data-driven Enterprise 85

Jet Global

MAY 16, 2022

You’ll be able to automatically roll over reports to the next period, with the latest data, to jump start the report creation process. Build documents from pre-existing sections, allowing experts to focus on their individual components. You’ll have consistency across internal and external reporting.

Finance 52

Finance Reporting Management Software 52

Ontotext

JUNE 10, 2021

They should be able to continuously integrate data across multiple internal systems and link it to data from external sources. To be able to automate these operations and maintain sufficient data quality, enterprises have started implementing the so-called data fabrics , that employ diverse metadata sourced from different systems.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Sisense

FEBRUARY 10, 2021

The right data, the right platform, the right partner. The experts at Sisense live and breathe data analytics — and the Sisense platform is designed from the ground up to connect with disparate datasets and infuse insight from those sources anywhere users need them.

Dashboards 52

Dashboards Enterprise Risk Software 52

Domino Data Lab

JULY 21, 2019

The approach is to provide remote access for government analysts and researchers to confidential data in a secure data facility and to build analytical capacity and collaborations through an Applied Data Analytics training program. What am I talking about with the new types of data? Transcript.

Metadata 65

Metadata Statistics Risk Machine Learning 65

Grooper

AUGUST 19, 2019

Recognizing text and certain features of a document require training as well. Data science, combined with ML technologies, gives organizations the ability to deliver relevant, timely insights to decision makers. From here on out, I’ll refer to ML and data science as just AI. Data science approaches. Data quality.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Andrew White

MARCH 22, 2019

Too many vendors have convinced their clients they have information stewards when fact they have more data quality analysts. Across all kinds of data such as structured and unstructured, analytics, algorithms, information, documents, images, and so on. Some don’t understand the difference. It is a great question.

Analytics 68

Analytics Metadata Data Governance Management 68

Andrew White

JANUARY 9, 2022

To drive a successful Data Analytics strategy do you think it is a multidisciplinary activity and if so, what additional roles would you expect to see involved. I would have to admit that there are few documents that talk about all the connections across any set of topics. We write about data and analytics.

Analytics 64

Analytics Measurement Modeling Data-driven 64