O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Some machine learning approaches (and many software engineering practices) are simply not appropriate for near-real time applications. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 116

Cost-Benefit Internet of Things Data-driven Data Lake 116

CIO Business Intelligence

SEPTEMBER 2, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Other sought-after skills include Python, R, JavaScript, C++, Apache Spark, and Hadoop. .

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Other sought-after skills include Python, R, JavaScript, C++, Apache Spark, and Hadoop. .

Finance 98

Finance IT Software Reporting 98

FineReport

MARCH 24, 2024

Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings. Certified Analytics Professional (CAP) , providing advanced insights into converting data into actionable insights.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers.

Analytics 128

Analytics Data Science Statistics Unstructured Data 128

CIO Business Intelligence

MARCH 29, 2022

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. And the problem is not just a matter of too many copies of data.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Sisense

OCTOBER 29, 2020

“Data is a critical factor in getting to where we need to be,” explained Ramsey. AVs are the most advanced version of artificial intelligence (AI) that we are working on right now and require an enormous amount of data to do machine learning to improve the computer’s ability to understand the world and make decisions.

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

bridgei2i

MARCH 11, 2021

The key to taking advantage of AI tools for small businesses is data. Easily understandable, highly curated, and reliable data helps Machine Learning (ML) tools evolve. As long as small businesses don’t have efficient data governance strategies, they can’t properly use AI and ML-powered tools. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

FEBRUARY 13, 2020

A modern data catalog includes many features and functions that all depend on the core capability of cataloging data—collecting the metadata that identifies and describes the inventory of shareable data. It is impractical to attempt cataloging as a manual effort.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Sisense

OCTOBER 15, 2020

As real-time analytics and machine learning stream processing are growing rapidly, they introduce a new set of technological and conceptual challenges. Every data professional knows that ensuring data quality is vital to producing usable query results.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Smart Data Collective

SEPTEMBER 22, 2021

Experts continue to raise concerns about how and if businesses are making use of unstructured data, but in addition to actively sharing that information, until access to machine learning protocols is more widespread, the ability to effectively utilize this information and derive insights will be compromised.

Unstructured Data 114

Unstructured Data Management Cost-Benefit Finance 114

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. Think about it – we have the top experts in the world in this company – experts at identifying use cases, building out clusters, ingesting data, and helping our customers with advanced analytics and machine learning.

Data-driven 43

Data-driven Data Quality Risk Interactive 43

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 71

Data Governance Strategy Enterprise Machine Learning 71

O'Reilly on Data

OCTOBER 22, 2020

The safest course of action is also the slowest and most expensive: obtain your training data as part of a collection strategy that includes efforts to obtain the correct representative sample under an explicit license for use as training data. How I use it: I like to ask this as early as possible. How many people will use it?

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. This is aligned to the five pillars we discuss in this post.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

Timo Elliott

JANUARY 22, 2019

Machine learning everywhere. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. Augmented analytics platforms based on cloud technology and machine learning are breaking down the longest-standing barriers to analytics success.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ).

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

CIO Business Intelligence

NOVEMBER 28, 2023

“By recognizing milestones, leaders give other stakeholders visibility into the progress being made, and also ensure that their team members feel appreciated for the level of effort they are putting in to make unstructured data actionable.” Quality is job one. Another key to success is to prioritize data quality.

Unstructured Data 128

Unstructured Data Data-driven Visualization Data Quality 128

Jedox

NOVEMBER 17, 2022

Manual, repetitive tasks being replaced by automated processes is definitely not new, but the impact of this on the accounting field leveraged through Artificial Intelligence (AI) and Machine Learning (ML) is still relatively new. The demands on the accounting industry have changed considerably in recent years.

Finance 75

Finance Cost-Benefit Forecasting Reporting 75

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams. Friction ensued.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

FineReport

JULY 18, 2022

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. Its core product Qlik Sense can connect data from numerous data sources.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

BI-Survey

NOVEMBER 24, 2020

It not only increases the speed and transparency of decisions and their quality, but it is also the foundation for the use of predictive planning and forecasting powered by statistical methods and machine learning. Faster information, digital change and data quality are the greatest challenges.

Forecasting 94

Forecasting Predictive Modeling Statistics Data-driven 94

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. 5) Data Analytics Made Accessible, by Dr. Anil Maheshwari. Best for : the new intern who has no idea what data science even means.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

MARCH 17, 2021

Key Features of a Machine Learning Data Catalog. Data intelligence is crucial for the development of data catalogs. At the center of this innovation are machine learning data catalogs (MLDCs). Unlike standalone tools, machine learning data catalogs have features like: Data search.

Machine Learning 52

Machine Learning Metadata Data Governance Interactive 52

The Unofficial Google Data Science Blog

JULY 18, 2023

Measurement challenges Assessing reliability is essentially a process of data collection and analysis. To do this, we collect multiple measurements for each unit of observation, and we determine if these measurements are closely related. In this case, the scale is not measuring the construct that interests us.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Testing Modeling 261

Alation

MARCH 24, 2021

The third installment of the quarterly Alation State of Data Culture Report was recently released, highlighting the data challenges enterprises face as they continue investing in artificial intelligence (AI). AI fails when it’s fed bad data, resulting in inaccurate or unfair results.

Reporting 105

Reporting Data Quality Business Driver Enterprise 105

datapine

JANUARY 31, 2022

As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214