Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Sisense

DECEMBER 3, 2019

The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. The first wave of digital transformations saw a dramatic decrease in data storage costs. On-demand compute resources and MPP cloud data warehouses emerged. Optimize raw data using materialized views.

Embedded Analytics 90

Embedded Analytics Data Warehouse Digital Transformation Digital 90

Astera

APRIL 7, 2023

Finally, the stored data is retrieved at optimal speeds to support efficient analysis and decision-making. Essentially, a data warehouse also acts as a centralized database for storing structured, analysis-ready data and giving a holistic view of this data to decision-makers.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

DECEMBER 21, 2022

The 2020 Global State of Enterprise Analytics report reveals that 59% of organizations are moving forward with the use of advanced and predictive analytics. For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Sisense

MAY 31, 2020

So when we learned we’d been honored with our fourth perfect recommendation score in Dresner’s 2020 Wisdom of Crowds BI Market Study , it was quite a thrill. Re-architecting Sisense into its current cloud-native form delivers even better connections to a cloud data warehouse, which almost every company is using or will use soon.

Data Warehouse 98

Data Warehouse Predictive Analytics Innovation Vision 98