Precisely

MAY 1, 2023

Virtually every enterprise on the planet invests heavily in data. Integration, data quality, data governance, location intelligence, and enrichment are driving trust and delivering value. How can organizations maximize their ROI on their investments in data integrity?

Food 52

Food Consulting Manufacturing Pharmaceutical 52

Databand.ai

JUNE 20, 2023

To achieve data integrity, organizations must implement various controls, processes, and technologies that help maintain the quality of data throughout its lifecycle. These measures include data validation, data cleansing, data integration, and data security, among others.

Data Integration 52

Data Integration Data Validation Pharmaceutical Data Cleanse 52

AltexSoft

NOVEMBER 23, 2021

Implementing data virtualization requires fewer resources and investments compared to building a separate consolidated store. Enhanced data security and governance. All enterprise data is available through a single virtual layer for different users and a variety of use cases. ETL in most cases is unnecessary.

Process 69

Process Data Lake Metadata Data Warehouse 69

Databand.ai

DECEMBER 13, 2022

He is constantly seeking out knowledge and being excited by the challenge of learning something new in the data science space. His most passionate topics include MLOps, machine learning, data quality and data governance. You can also watch the video recording.

Data Engineer 52

Data Engineer Data Engineering Engineering AWS 52

Cloudera

AUGUST 8, 2024

Cloudera’s data lakehouse provides enterprise users with access to structured, semi-structured, and unstructured data, enabling them to analyze, refine, and store various data types, including text, images, audio, video, system logs, and more.

Pharmaceutical 71

Pharmaceutical Unstructured Data Government Data Ingestion 71

AltexSoft

MARCH 30, 2023

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. Multi-level data security Databricks was designed with security in mind.

Scala 64

Scala Data Lake BI Machine Learning 64