FineReport

APRIL 26, 2023

Having visually appealing graphics can also increase user adoption. Advanced analytics capabilities : The tool should be able to analyze data and identify patterns, as well as forecast future events with complex forecasting algorithms, going beyond simple mathematical calculations.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

CIO Business Intelligence

SEPTEMBER 2, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

IBM Big Data Hub

DECEMBER 16, 2022

Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information. She can search structured or unstructured data, visualizations and dashboards, machine learning models, and database connections.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

FEBRUARY 15, 2024

Improved data accessibility: By providing self-service data access and analytics, modern data architecture empowers business users and data analysts to analyze and visualize data, enabling faster decision-making and response to regulatory requirements.

Insurance 86

Insurance Data Architecture Risk Management Risk 86

Ontotext

FEBRUARY 26, 2024

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. Here’s how our tool makes it work. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration .

Testing 307

Testing Machine Learning Consulting Data Quality 307

Sisense

JULY 22, 2020

In all cases the data will eventually be loaded into a different place, so it can be managed, and organized, using a package such as Sisense for Cloud Data Teams. Using data pipelines and data integration between data storage tools, engineers perform ETL (Extract, transform and load).

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Cloudera

MAY 16, 2018

All three cases require a “big picture” approach that incorporates new and alternative data sources and cross-functional collaboration throughout the organization not only to identify illegal activities, rogue traders, or personal misconduct but also to provide evidential material that demonstrates a deep understanding of the intent.

Data Lake 42

Data Lake Risk Visualization Unstructured Data 42

Cloudera

SEPTEMBER 6, 2018

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. The foundation of this end-to-end AML solution is Cloudera Enterprise.

Machine Learning 40

Machine Learning Risk Big Data Unstructured Data 40

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Rely on interactive data visualizations. For decades now, data analytics has been considered a segregated task. Because it is that important. Let’s see this with an example of a sales dashboard.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. .

Data Processing 91

Data Processing Data Warehouse Enterprise Visualization 91

Jet Global

MAY 9, 2024

Real-Time Analytics Pipelines : These pipelines process and analyze data in real-time or near-real-time to support decision-making in applications such as fraud detection, monitoring IoT devices, and providing personalized recommendations. For example, migrating customer data from an on-premises database to a cloud-based CRM system.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52