ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

DECEMBER 23, 2022

For example, Online Analytical Processing (OLAP) systems only allow relational data structures so the data has to be reshaped into the SQL-readable format beforehand. In ELT, raw data is loaded into the destination, and then it receives transformations when it’s needed. ELT allows them to work with the data directly.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

OCTOBER 29, 2021

Since then, many other well-loved terms, such as “data economy,” have come to be widely used by industry experts to describe the influence and importance of big data in today’s society. Accuracy Accuracy refers to how well the information recorded reflects a real event or object. Nonparametric.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

DoorDash Engineering

APRIL 12, 2023

As we mentioned in our previous blog , we began with a ‘Bring Your Own SQL’ method, in which data scientists checked in ad-hoc Snowflake (our primary data warehouse) SQL files to create metrics for experiments, and metrics metadata was provided as JSON configs for each experiment.

SQL 82

SQL Metadata Raw Data Government 82

AltexSoft

MARCH 14, 2023

Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data.

IT 59

IT Data Warehouse Data Governance Data Lake 59