CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer vs. data architect.

Analytics 121

Analytics Data Science Statistics Unstructured Data 121

Jedox

OCTOBER 22, 2020

Other challenges to data analytics include data storage, data quality, and a lack of knowledge and tools necessary to make sense of the data and generate those critical insights. Limited real-time analytics and visuals. Typically, we take our multiple data sources and perform some level of ETL on the data.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 69

Data Quality Data Integration Metadata Cost-Benefit 69

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Database specialists may be charged with looking after other data repositories used by the organization, such as data stores, marts, warehouses, and lakes.

Statistics 97

Statistics Metrics Visualization Finance 97

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Data Architecture 82

Data Architecture Cost-Benefit Digital Transformation Business Driver 82

IBM Big Data Hub

SEPTEMBER 7, 2022

We recommend that data leaders pick a small problem and solve that, then look at the impact. Do your data governance systems desperately need an overhaul or is your data visualization in need of a spruce up? Do you accept that data science takes a slight back seat while you improve the data quality?

Data Strategy 52

Data Strategy Strategy Data-driven Data Quality 52

CIO Business Intelligence

FEBRUARY 20, 2023

To earn the Salesforce Data Architect certification , candidates should be able to design and implement data solutions within the Salesforce ecosystem, such as data modelling, data integration and data governance.

Consulting 60

Consulting B2B Cost-Benefit Sales 60

Smart Data Collective

FEBRUARY 23, 2021

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

Big Data 116

Big Data Visualization Data Quality Data-driven 116

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 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 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 89

Management Metadata Data Architecture Data Lake 89

IBM Big Data Hub

DECEMBER 4, 2023

For organizations embarking on a digital transformation , it’s crucial to visualize how an ERP system will integrate with every aspect of a business’ operations. During configuration, an organization constructs its data architecture and defines user roles. Check that the data conforms to the dedicated data hierarchy.

Testing 81

Testing Consulting Digital Transformation Cost-Benefit 81

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

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

BI-Survey

FEBRUARY 6, 2020

ML helps users prepare data to enhance reports and to select appropriate data visualizations in visual analysis and dashboards. Architectures and modern tools which enable business users to search, prepare and analyze data will pave the way to reacting promptly to market changes.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

AWS Big Data

APRIL 5, 2023

In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals. Each of these tools were getting data from a different place, and that’s where it gets difficult,” says Jeroen Minnaert, head of data at Showpad. “If

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52