Ontotext

FEBRUARY 12, 2024

As organizations become more data-driven, different use cases will always require different types of transformations, putting a heavy load on the centralized teams. For large enterprises, data mesh distributes data ownership and reduces dependencies between services.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

datapine

SEPTEMBER 29, 2022

Paired to this, it can also: Improved decision-making process: From customer relationship management, to supply chain management , to enterprise resource planning, the benefits of effective DQM can have a ripple impact on an organization’s performance. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

MARCH 14, 2024

Microsoft recently introduced a comprehensive analytics solution for its enterprise customers, Microsoft Fabric. The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

JULY 19, 2023

Data Connectivity Enhancements Data and content authors are the first users in the app building infrastructure and content. It is important for our customers to access advanced connectors and data transformation features so they can build a robust data layer.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

AWS Big Data

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 89

Data Lake Snapshot Big Data Data-driven 89

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

Cost-Benefit 82

Cost-Benefit Metadata Optimization Management 82

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 85

Data Lake Data Architecture Metadata Data Warehouse 85

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

Jet Global

MAY 1, 2023

Traditional BI Platforms Traditional BI platforms are centrally managed, enterprise-class platforms. These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

AUGUST 3, 2023

And at First Commerce Bank, EVP and COO Gregory Garcia hopes to leverage unified, real-time data to monitor risks such as worsening vacancy rates that could make it harder for commercial property owners to pay their mortgages. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 95

Analytics Data Lake Metadata Cost-Benefit 95

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 90

Data Processing Data Warehouse Enterprise Visualization 90

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 65

Data Lake Metadata Cost-Benefit Data Warehouse 65