Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

FEBRUARY 27, 2024

Governance and self-service – The Bluestone Data Platform provides a governed, curated, and self-service avenue for all data use cases. AWS services like AWS Lake Formation in conjunction with Atlan help govern data access and policies. Ben Vengerovsky is a Data Platform Product Manager at Bluestone.

Data-driven 97

Data-driven Data Lake Data Quality Data Governance 97

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. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 95

Data Lake Unstructured Data Data Warehouse Data Quality 95

Peter James Thomas

AUGUST 2, 2019

Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment. Data Federation. Data Function. Data Model. Data Operating Model. Thanks to all of these for their help. Application Programming Interface (API).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 81

Management Metadata Data Architecture Data Lake 81

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. 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.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Are problems with data tests? Which report tab is wrong?

Testing 130

Testing Data Governance Data Quality Data-driven 130

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value. Of course, no set of imperatives for a data strategy would be complete without the need to consider people, process, and technology.

Data Strategy 98

Data Strategy Strategy Visualization Consulting 98

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.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

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. It’s raw, unprocessed data straight from the source. usr/local/airflow/.local/bin/dbt

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

CIO Business Intelligence

AUGUST 9, 2022

Data engineers and data scientists often work closely together but serve very different functions. Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data engineer vs. data architect.

Analytics 116

Analytics Data Science Statistics Unstructured Data 116

IBM Big Data Hub

JANUARY 25, 2023

Breaking down these silos to encourage data access, data sharing and collaboration will be an important challenge for organizations in the coming years. The right data architecture to link and gain insight across silos requires the communication and coordination of a strategic data governance program.

Data Governance 52

Data Governance Data-driven Strategy Management 52

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? Why Do You Need an Enterprise Analytics Strategy?

Strategy 52

Strategy Enterprise Analytics Data Governance 52

BI-Survey

FEBRUARY 6, 2020

Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data. These problems become even more obvious when contrasted with modern infrastructures built in the cloud and micro services as well as the challenges caused by exploding data volume and variety.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. From there, it can be easily accessed via dashboards by data consumers or those building into a data product.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

Ontotext

FEBRUARY 26, 2024

Main Takeaways Graph technologies have the potential to deliver on the key goals and aspirations of every organization seeking to be data-driven. This is becoming increasingly important as we enter the age of AI where data quality, context, and trust really matter.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

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. Have a look at this and see if this helps: Data, Analytics and AI Form the Foundation of Data-Driven Decision Making. . We write about data and analytics.

Analytics 64

Analytics Measurement Modeling Data-driven 64