Anmut

MARCH 24, 2022

After decades in the background, data is currently king of the business world. Visionary companies like Google and Amazon are renowned for figuring out the transformational power of data, using data-driven business models to achieve extraordinary success. It doesn’t have to be this way.

ROI 52

ROI Measurement Data-driven Data Transformation 52

Peter James Thomas

OCTOBER 30, 2018

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. It may be to introduce or expand Data Governance.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 94

Dashboards Analytics Metadata Optimization 94

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 83

Data Lake Data Architecture Metadata Data Warehouse 83

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 84

Enterprise Data Warehouse Data Lake Optimization 84

IBM Big Data Hub

JANUARY 18, 2023

Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. For these workloads, data lake vendors usually recommend extracting data into flat files to be used solely for model training and testing purposes.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Peter James Thomas

MARCH 9, 2020

I last wrote about the process of creating a Data Strategy back in 2014 and – with the many changes that the field has seen since then – am overdue publishing an update, so watch this space. Such a model presents a series of states into which an organisation may fall with respect to its data.

Measurement 67

Measurement Strategy Data Strategy Modeling 67

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. This data is then used by various applications for streaming analytics, business intelligence, and reporting. This ensures that the data is suitable for training purposes.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The company needed a modern data architecture to manage the growing traffic effectively. .

Data Lake 76

Data Lake Data Warehouse Data Architecture Reporting 76

erwin

APRIL 16, 2024

The data mesh approach distributes data ownership and decentralizes data architecture, paving the way for enhanced agility and scalability. With distributed ownership there is a need for effective governance to ensure the success of any data initiative. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

CIO Business Intelligence

AUGUST 3, 2023

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Ontotext

FEBRUARY 12, 2024

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 88

Data Lake Data Warehouse B2B Data-driven 88

Birst BI

FEBRUARY 25, 2020

Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. Data never leaves Snowflake with Birst’s ability to support the reporting and self-service needs of both centralized IT and decentralized LOB teams.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

DataKitchen

JANUARY 23, 2023

Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. This is especially true in the case of the one-to-many, producer-to-consumer relationships we have on our data architecture. Are problems with data tests? Which report tab is wrong? When did it last run?

Testing 130

Testing Data Governance Data Quality Data-driven 130

AWS Big Data

APRIL 5, 2023

QuickSight would help local data stewards, who weren’t technical but knew the use cases intimately, to create their own dashboards and prototype them with their customers before promoting them through the product. The serverless model was also compelling because we did not have to pay for server instances nor license fees per reader.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52