O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 362

Marketing Experimentation Metrics Testing 362

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 125

Analytics Data Science Statistics Unstructured Data 125

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. Data has long been important to the financial industry — it’s a vital component that helps inform everything from the stock market to personal bank accounts.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. Data has long been important to the financial industry — it’s a vital component that helps inform everything from the stock market to personal bank accounts.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

APRIL 29, 2022

In this new era the role of humans in the development process also changes as they morph from being software programmers to becoming ‘data producers’ and ‘data curators’ – tasked with ensuring the quality of the input. Further, data management activities don’t end once the AI model has been developed.

Data Governance 144

Data Governance IT Risk Data Lake 144

Smart Data Collective

APRIL 20, 2022

An automated data profiling tool can discover and filter potentially inaccurate values while marking the information for further investigation or assessment. It aids in the identification of erroneous data and its sources. Standardizing the data collecting and data input process can go a long way toward ensuring optimal accuracy.

Data Processing 136

Data Processing Data Collection Technology Optimization 136

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 112

Cost-Benefit Internet of Things Data-driven Data Lake 112

DataKitchen

MARCH 16, 2023

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage. Cleaning up dirty data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

erwin

JUNE 11, 2020

Data intelligence transforms the way industries operate by enabling businesses to hasten the process of analyzing and understanding the derived information with its more understandable models and aggregated trends. UPS employed the Orion route optimization system and was able to cut down 364 million miles from its routes globally.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

bridgei2i

MARCH 11, 2021

Creating an efficient data governance strategy means – Breaking down all sources of accumulated data across the organization. Recognizing the “right” data that can be optimized by AI-powered business analytics tools. Identify data errors and eliminate them from the system. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Ontotext

AUGUST 23, 2021

Many of the data exchange processes on the electrical grid are (or would benefit from being) carried out with Web standards. But what has the electrical grid to do with data exchange on the Web, integration and interoperability?

Marketing 52

Marketing Data Quality Modeling Management 52

FineReport

MAY 31, 2023

Contemporary dashboards surpass basic visualization and reporting by utilizing financial analytics to amalgamate diverse financial and accounting data, empowering analysts to delve further into the data and uncover valuable insights that can optimize cost-efficiency and enhance profitability.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another.

Statistics 97

Statistics Metrics Visualization Finance 97

O'Reilly on Data

MARCH 31, 2020

At measurement-obsessed companies, every part of their product experience is quantified and adjusted to optimize user experience. These companies eventually moved beyond using data to inform product design decisions. That foundation means that you have already shifted the culture and data infrastructure of your company.

Management 332

Management Machine Learning Experimentation Metrics 332

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 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

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 69

Data Lake Data Governance Data Warehouse Data Processing 69

Smart Data Collective

SEPTEMBER 21, 2021

The increased amounts and types of data, stored in various locations eventually made the management of data more challenging. Challenges in maintaining data. As organizations keep using several applications, the data collected becomes unmanageable and inaccessible in the long run. Data quality and governance.

Management 105

Management Internet of Things Data Quality Data Integration 105

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

IBM Big Data Hub

SEPTEMBER 11, 2023

A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 89

Data-driven IT Measurement Cost-Benefit 89

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s. Security: It must serve data throughout a system.

Data Governance 88

Data Governance Metadata Data-driven Enterprise 88

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff! This is sub-optimal. Optimal Analytics Team Org Structure.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. I can use that to hypothesize what an optimal budget allocation might look like. Dealing with data quality doubt is every day and, sadly, very complex challenge for many, if not most, of us.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

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. Comprehensive governance and data transparency policies are essential.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. The problems down in the mature bucket, those are optimizations, they aren’t showstoppers. Machine learning is a subset of mathematical optimization. How can you trace that all the way back into the data collection?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JUNE 23, 2019

Google, Facebook, other leaders, they really have set up a culture of extreme measurement where every part of their product experience is instrumented to optimize clicks and drive user engagement. The biggest time sink is often around data collection, labeling and cleaning.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

APRIL 21, 2014

The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. We wonder why data people are not loved. :). Let's end on that note of optimism. Six years go by. Nothing changes for the business.

Marketing Analytics 131

Marketing Analytics Marketing Analytics Measurement 131

Andrew White

JANUARY 9, 2022

– We see most, if not all, of data management being augmented with ML. Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration.

Analytics 64

Analytics Measurement Modeling Data-driven 64

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

Domino Data Lab

FEBRUARY 4, 2019

These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection. You’ll need to read the papers.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

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 and analytics allow users to know their businesses on a deeper level.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

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

FEBRUARY 22, 2022

In the article, he pointed to a pretty fascinating trend: “Experian has predicted that the CDO position will become a standard senior board-level role by 2020, bringing the conversation around data gathering, management, optimization, and security to the C-level.” We love that data is moving permanently into the C-Suite.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

MARCH 17, 2021

According to the Forrester Wave: Machine Learning Data Catalogs, Q4 2020 , “Alation exploits machine learning at every opportunity to improve data management, governance, and consumption by analytic citizens. Tracking and Scaling Data Lineage. Data stewards are then alerted and the process is formalized transparently.

Machine Learning 52

Machine Learning Metadata Data Governance Interactive 52

Alation

NOVEMBER 11, 2021

Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance? Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

datapine

APRIL 16, 2019

The importance of data in decision lies in consistency and continual growth. It enables companies to create new business opportunities, generate more revenue, predict future trends, optimize current operational efforts, and produce actionable insights. 3) Gather data now. 6) Analyze and understand.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287