IBM Big Data Hub

JANUARY 5, 2023

Practice proper data hygiene across interfaces. How to build a data architecture that improves data quality. A data strategy can help data architects create and implement a data architecture that improves data quality. Steps for developing an effective data strategy include: 1.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Laminar Security

AUGUST 21, 2023

In this blog, we will delve into the key insights from the report and emphasize the significance of DSPM in shaping the data security industry. The Shifting Data Security Landscape Cloud service providers (CSPs) have revolutionized data analytics and data pipelines, presenting data security teams with novel challenges.

Management 40

Management Risk Unstructured Data Data Strategy 40

BizAcuity

APRIL 14, 2022

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. Data Management. Unscalable data architecture. Product/Service innovation.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Why is data analytics important for travel organizations?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

JULY 29, 2022

Is yours among the organizations hoping to cash in big with a big data solution? Organizations have good reason to believe that adopting data analytics tools and hiring data professionals will allow them to extract the full value of their data. Read on to be sure you set yourself up for success. .

Data Architecture 87

Data Architecture Data Strategy Risk Management Strategy 87

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Grooper

AUGUST 19, 2019

Master data management. Data governance. Structured, semi-structured, and unstructured data. Data pipelines. Business Analytics. Business analytics is a focus on practical requirements needed for understanding current performance and for predicting future outcomes. Databases, tables, and columns.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Sisense

JULY 23, 2021

We focus on the core games management systems, which generate a lot of key operational data, so we’ve been naturally a lot more inquisitive of those datasets. We are focused on unpicking them, really analyzing them to understand what they tell us about Games optimization.”. Data will create a better-connected future.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

Alation

FEBRUARY 10, 2022

Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification? Either completed manually or using automation, the data classification process is based on the data’s context, content, and user discretion.

Data Governance 52

Data Governance Risk Insurance Metadata 52

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

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. Gain visibility into data history.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52