Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

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. Data Warehouse. Data cleaning is a vital data skill as data comes in imperfect and messy types.

Data Lake 106

Data Lake Data Warehouse Unstructured Data Big Data 106

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. Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

JULY 23, 2021

At the Information, Knowledge, and Games Learning (IKL) unit, we anticipate collecting about 1TB of data from primary sources. This analytics engine will process both structured and unstructured data. “We There are some amazing opportunities to get incredibly granular analytics from the venues there.”.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105