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 364

Marketing Experimentation Metrics Testing 364

Smart Data Collective

DECEMBER 7, 2020

Since the market for big data is expected to reach $243 billion by 2027 , savvy business owners will need to find ways to invest in big data. Artificial intelligence is rapidly changing the process for collecting big data, especially via online media. The Growth of AI in Web Data Collection.

Data Collection 95

Data Collection Data Quality Big Data Machine Learning 95

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 Data Quality 52

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. Top 15 data science bootcamps. Data Science Dojo. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

SEPTEMBER 30, 2024

Emphasizing ethics and impact Like many of the government agencies it serves, Mathematica started its cloud journey on AWS shortly after Bell arrived six years ago and built the Mquiry data collection, collaboration, management, and analytics platform on the Mathematica Cloud Support System for its myriad clients.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

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

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 96

Analytics Machine Learning Unstructured Data Business Intelligence 96

CIO Business Intelligence

NOVEMBER 22, 2022

“Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.” The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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

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 Data Lake Risk 145

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 75

Data Governance Strategy Enterprise Machine Learning 75

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 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

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 131

Analytics Data Science Statistics Unstructured Data 131

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 363

Consulting Risk Cost-Benefit Modeling 363

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

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

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 130

Unstructured Data Data-driven Visualization Data Quality 130

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

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

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

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

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 79

Data Architecture Data Lake Data Warehouse Metadata 79

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 79

Data Strategy Strategy Data Warehouse Prescriptive Analytics 79

Alation

MARCH 5, 2021

How Alation Activates Data Governance. Why is Data Governance Important? As data collection and storage grow, so too does the need for data governance. Where data governance once focused primarily on compliance, the age of big data has broadened its applications. Data Governance Roles.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

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 135

Unstructured Data Management Cost-Benefit Machine Learning 135

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

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

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 77

Finance Cost-Benefit Forecasting Reporting 77

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

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

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

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

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Data lineage features.

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

OCTOBER 12, 2021

Nowadays, machine learning , AI, and augmented reality analytics are speeding up this process, so that collection and analysis are always on. Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Evaluate and monitor data quality.

Strategy 52

Strategy Enterprise Analytics Data Governance 52