Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

FineReport

JUNE 24, 2021

Originally, Excel has always been the “solution” for various reporting and data needs. However, along with the diffusion of digital technology, the amount of data is getting larger and larger, and data collection and cleaning work have become more and more time-consuming. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

O'Reilly on Data

DECEMBER 19, 2018

We won’t be writing code to optimize scheduling in a manufacturing plant; we’ll be training ML algorithms to find optimum performance based on historical data. With machine learning, the challenge isn’t writing the code; the algorithms are implemented in a number of well-known and highly optimized libraries.

Machine Learning 258

Machine Learning Software Metadata Testing 258

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Timo Elliott

JANUARY 22, 2019

Compliance drives true data platform adoption, supported by more flexible data management. As it has been for the last forty years, data collection, preparation, and standardization remain the most challenging aspects of analytics. Traditional analytics focused on structured data flowing from operational systems.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

Smart Data Collective

JUNE 11, 2019

Big data means using a wired or wireless connection to track machine utilization with greater accuracy to see the variables that could impact its performance. A manager can see what or who is performing optimally, giving the information needed when making business decisions. Improved Strategic Decision-Making.

Manufacturing 93

Manufacturing Analytics Big Data Data mining 93

IBM Big Data Hub

AUGUST 28, 2023

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis. positive, negative or neutral).

Data mining 54

Data mining Machine Learning Deep Learning Marketing 54

Sisense

JULY 23, 2021

We focus on the core games management systems, which generate a lot of key operational data, so we’ve been naturally a lot more inquisitive of those datasets. We are focused on unpicking them, really analyzing them to understand what they tell us about Games optimization.”. The results have been highly valuable.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

Jet Global

MAY 9, 2024

ELT can simplify the data pipeline by reducing the number of steps and tools involved, but it may rely on the destination system’s ability to handle complex transformations effectively. In an ETL process, data transformations can be optimized before loading, which may improve performance for data-intensive transformations.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

FineReport

FEBRUARY 5, 2020

To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department. Some people pay attention to functions and interaction effects, such as data collection, image and video collection, positioning, linkage and drilling on the mobile devices.

Metadata 98

Metadata Dashboards Informatics Visualization 98

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. Bringing the power of AI to IoT.

IoT 56

IoT Internet of Things Big Data Data-driven 56

AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. This method uses GZIP compression to optimize storage consumption and query performance. You’re now ready to query the tables using Athena.

Analytics 97

Analytics IoT Metadata Internet of Things 97

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Sawzall is a programming language developed at Google for performing aggregation over the result of complex operations on structured data. However, it turns out to be quite useful for data science applications.

Data Science 56

Data Science Statistics Testing Metadata 56