Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. Where data flows, ideas follow.

IT 106

IT Data Architecture Unstructured Data Big Data 106

CIO Business Intelligence

SEPTEMBER 14, 2023

Data engineers also need communication skills to work across departments and to understand what business leaders want to gain from the company’s large datasets. Data engineers must also know how to optimize data retrieval and how to develop dashboards, reports, and other visualizations for stakeholders.

Analytics 132

Analytics Data Science Unstructured Data Data mining 132

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

CIO Business Intelligence

JUNE 23, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. But this is not your grandfather’s big data.

IT 77

IT Data Architecture Unstructured Data Big Data 77

Ontotext

JANUARY 29, 2024

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. Without this, organizations will continue to pay a “bad data tax” as AI/ML models will struggle to get past a proof of concept and ultimately fail to deliver on the hype.

Strategy 52

Strategy Management Metadata Data-driven 52

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 123

Analytics Data Science Statistics Unstructured Data 123

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

Sisense

SEPTEMBER 15, 2020

Now companies with on-premises data can enjoy cloud-style benefits in a truly hybrid setup. In this article, we’ll explore what that looks like and how users can connect AWS Outposts to Sisense to get more out of their data. Analytics & BI users: Better queries, greater efficiency, different data types.

Key Performance Indicator 79

Key Performance Indicator Cost-Benefit Unstructured Data Strategy 79

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. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

CIO Business Intelligence

MARCH 29, 2022

An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists. New approaches are being developed to understand and use unstructured data, for instance. Reducing data waste. About Ellen Friedman.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 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 83

Data Architecture Data Strategy Risk Management Strategy 83

CIO Business Intelligence

MAY 24, 2022

Organisations have to contend with legacy data and increasing volumes of data spread across multiple silos. To meet these demands many IT teams find themselves being systems integrators, having to find ways to access and manipulate large volumes of data for multiple business functions and use cases.

Data-driven 82

Data-driven Data Lake Data Warehouse Cost-Benefit 82

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-driven Data Science 54

Sisense

JULY 23, 2021

“We are also working to factor in the COVID impact when making sense of the data and, more importantly, when communicating it.”. Chris and his team are increasing the volume of data being captured and using automation to augment their data strategy : “This is a real jump forward for us.

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 Strategy 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 62

Data Architecture Data Lake Machine Learning Data Governance 62

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