Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

erwin

MARCH 4, 2021

And when you talk about that question at a high level, he says, you get a very “simple answer,”– which is ‘the only thing we want to have is the right data with the right quality to the right person at the right time at the right cost.’. The Why: Data Governance Drivers. Why should companies care about data governance?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

Sisense

DECEMBER 12, 2019

Yet with this surge in data, many organizations are either not able to draw insights from their data, or are not able to do so quickly enough. It is estimated that of all data collected, less than 1% is actually analyzed and used. Your data is a gold mine and you’re barely scratching the surface of its value!

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

Occam's Razor

OCTOBER 19, 2010

Move from a data collection obsession and develop a crush on data analysys. With simple configuration updates in the tools you'll create a custom report showing you Source/Campaign, Visits –> Live Chat % –> Goal Conversion Rate –> Per Visit Goal Value. of these three tools: ~ Yahoo! Three tools.

Analytics 135

Analytics Testing Measurement Optimization 135

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

DataKitchen

JANUARY 23, 2023

For example, a data error may only be apparent when combined with other data or used in a specific analysis or report. Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. Which report tab is wrong? Which production job filled that report?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. These reports are critical to making decisions.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52