DataKitchen

JUNE 24, 2021

Bergh added, “ DataOps is part of the data fabric. You should use DataOps principles to build and iterate and continuously improve your Data Fabric. Automate the data collection and cleansing process. Education is the Biggest Challenge. “We

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

Alation

SEPTEMBER 1, 2022

By definition, a data intelligence platform must serve a wide variety of user types and use cases – empowering them to collaborate in one shared space. The problem Data Intelligence Platforms solve. Why is a data intelligence platform needed in the first place? Get the new IDC Marketscape for Data Catalogs to learn more.

Reporting 52

Reporting Metadata Data Governance Interactive 52

Alation

OCTOBER 12, 2022

Quantitative analysis can take two forms: the traditional business analysis of numerical data, or the more academic quantitative analysis. Traditional business analysis uses numerical methods to paint a picture, often through numerical methods, like statistics. What Is the Role of Statistics in Quantitative Data Analysis?

Statistics 52

Statistics Sales Testing Marketing 52

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Maybe they analyzed the metadata from pictures and found that there was a strong correlation between properties that rented often and expensive camera models.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Record-level program scope As a data scientist, you write a Sawzall script to operate at the level of a single record. The scope of each record is determined by the source of the data; it might be a web page, metadata about an app, or logs from a web server. Despite Sawzall's decline, these are still actively used today.

Data Science 57

Data Science Statistics Testing Metadata 57

AWS Big Data

JULY 3, 2023

It provides features such as ACID transactions on top of Amazon S3-based data lakes, schema evolution, partition evolution, and data versioning. With scalable metadata indexing, Apache Iceberg is able to deliver performant queries to a variety of engines such as Spark and Athena by reducing planning time.

Snapshot 94

Snapshot Data Lake Testing Strategy 94

Alation

APRIL 25, 2023

But whatever your industry, perfecting your processes for making important decisions about how to handle data is crucial. Whether you deal in customer contact information, website traffic statistics, sales data, or some other type of valuable information, you’ll need to put a framework of policies in place to manage your data seamlessly.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

But whatever your industry, perfecting your processes for making important decisions about how to handle data is crucial. Whether you deal in customer contact information, website traffic statistics, sales data, or some other type of valuable information, you’ll need to put a framework of policies in place to manage your data seamlessly.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Andrew White

JANUARY 9, 2022

We found anecdotal data that suggested things such as a) CDO’s with a business, more than a technical, background tend to be more effective or successful, and b) CDOs most often came from a business background, and c) those that were successful had a good chance at becoming CEO or CEO or some other CXO (but not really CIO).

Analytics 64

Analytics Measurement Data-driven Modeling 64

O'Reilly on Data

JULY 28, 2020

Acquiring data is often difficult, especially in regulated industries. Once relevant data has been obtained, understanding what is valuable and what is simply noise requires statistical and scientific rigor. Look for peculiarities in your data (for example, data from legacy systems that truncate text fields to save space).

Marketing 364

Marketing Experimentation Metrics Testing 364

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Anmut

OCTOBER 29, 2020

COVID-19 exposes shortcomings in data management. Getting consistency is also a daunting challenge in the face of a tsunami of data. Having a data-driven approach creates much sought after competitive advantage. To get consistent and reliable data, this is the kind of standardisation we need.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage. Put border controls in place.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance. What’s the best way to organize data and ensure it is supported by business policies and well-defined, governed systems, data elements and performance measures? Put border controls in place.

Measurement 96

Measurement Sales Data Governance Metadata 96

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book?—?for features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

Jet Global

MAY 1, 2023

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.” addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

DataKitchen

JANUARY 23, 2023

Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements. Data testing can be done through various methods, such as data profiling, Statistical Process Control, and quality checks.

Testing 130

Testing Data Governance Data Quality Data-driven 130