Smart Data Collective

SEPTEMBER 23, 2020

We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data. Many people are confused about these two, but the only similarity between them is the high-level principle of data storing.

Data Lake 135

Data Lake Data Warehouse Unstructured Data Big Data 135

CIO Business Intelligence

JANUARY 24, 2024

“Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake. What are the goals for leveraging unstructured data?”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

CIO Business Intelligence

JUNE 28, 2022

And then there is the rise of privacy concerns around so much data being collected in the first place. Following are some of the dark secrets that make data management such a challenge for so many enterprises. Unstructured data is difficult to analyze. Even structured data is often unstructured.

Management 138

Management Internet of Things Data-driven Statistics 138

Sisense

JULY 23, 2021

This analytics engine will process both structured and unstructured data. “We We are constantly collecting data from all kinds of different sources — whether it is a library of documents, analytics reports, pictures, or even videos,” says Chris.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

Sisense

OCTOBER 6, 2020

When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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