AWS Big Data

JULY 20, 2023

To overcome these issues, Orca decided to build a data lake. A data lake is a centralized data repository that enables organizations to store and manage large volumes of structured and unstructured data, eliminating data silos and facilitating advanced analytics and ML on the entire data.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

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 94

Data Processing Data Warehouse Enterprise Visualization 94

Sisense

MAY 11, 2021

With our strategy in mind, we factored in our consumers and consuming services, which primarily are Sisense Fusion Analytics and Cloud Data Teams. Interestingly, this ad hoc analysis benefits from a single source of truth that is easy to query to allow for quickly querying of raw data alongside the cleanest data (i.e.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Ontotext

MARCH 20, 2024

The Bridge to Unified Data and Growth Imagine a world where your sales and marketing teams can effortlessly access and utilize data from various sources – LinkedIn, ZoomInfo, DBpedia, Yahoo Finance, and even your internal data sources – all within the familiar interface of Salesforce.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Alation

NOVEMBER 22, 2022

This is why public agencies are increasingly turning to an active governance model, which promotes data visibility alongside in-workflow guidance to ensure secure, compliant usage. An active data governance framework includes: Assigning data stewards. Standardizing data formats. Improve data visibility.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

Jet Global

NOVEMBER 7, 2023

This growth is caused, in part, by the increasing use of cloud platforms for data storage and processing. But it is also a result of the surge in multimedia content in cloud repositories that requires tools and methods for extracting insights from rich, unstructured data formats.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

CIO Business Intelligence

MARCH 26, 2025

Give up on using traditional IT for AI The ultimate goal is to have AI-ready data, which means quality and consistent data with the right structures optimized to be effectively used in AI models and to produce the desired outcomes for a given application, says Beatriz Sanz Siz, global AI sector leader at EY.

Data Quality 129

Data Quality Forecasting Unstructured Data Data-driven 129

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

AWS Big Data

JANUARY 29, 2025

This configuration allows you to augment your sensitive on-premises data with cloud data while making sure all data processing and compute runs on-premises in AWS Outposts Racks. Additionally, Oktank must comply with data residency requirements, making sure that confidential data is stored and processed strictly on premises.

Big Data 89

Big Data Data Analytics Analytics Interactive 89

AWS Big Data

APRIL 28, 2025

Many organizations turn to data lakes for the flexibility and scale needed to manage large volumes of structured and unstructured data. Apache Spark on Amazon EMR handled data transformations and incremental updates, and Amazon DynamoDB maintained state, including synchronization checkpoints and table mappings.

Data Lake 67

Data Lake Metadata Cost-Benefit Snapshot 67