Analytics Vidhya

MAY 30, 2023

Introduction In the realm of machine learning, the veracity of data holds utmost significance in the triumph of models. Inadequate data quality can give rise to erroneous predictions, unreliable insights, and overall performance.

Machine Learning 288

Machine Learning Data Quality Modeling Analytics 288

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Dataiku

APRIL 19, 2021

Data needs to be valuable, thus of high quality , to drive machine learning model success.

Data Quality 105

Data Quality Machine Learning Modeling Management 105

CIO Business Intelligence

AUGUST 2, 2022

Data analytics and business intelligence are critical to every business, but especially important in the energy industry, as information is channeled from consumers and commercial clients related to usage that feeds into AES’ sustainability and services planning. The second is the data quality in our legacy systems.

Data Quality 92

Data Quality Digital Transformation Machine Learning Predictive Analytics 92

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 92

Data Quality Data Governance Data Lake Testing 92

DataKitchen

MAY 7, 2024

DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certificatio n (3 hours, online, free, signup online): DataOps Manifesto (over 30,000 signatures) One (..)

Data Quality 161

Data Quality Testing Consulting Metrics 161

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

AWS Big Data

JUNE 6, 2023

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

Data Quality 69

Data Quality Data Lake Visualization Data-driven 69

IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

Analytics Vidhya

FEBRUARY 20, 2023

Introduction Whenever we talk about building better forecasting models, the first and foremost step starts with detecting.

Forecasting 275

Forecasting Data Quality Modeling Analytics 275

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. A decentralized, flexible data processing infrastructure. Let’s take a look.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

APRIL 8, 2024

Nearly 10 years ago, Bill James, a pioneer in sports analytics methodology, said if there’s one thing he wished more people understood about sabermetrics, pertaining to baseball, it’s that the data is not the point. The point is to use the data like a razor to cut through false convictions to find the truth.

Analytics 112

Analytics Broadcasting Predictive Analytics Metrics 112

Analytics Vidhya

DECEMBER 28, 2022

Introduction In deep learning, the activation functions are one of the essential parameters in training and building a deep learning model that makes accurate predictions. Choosing the best appropriate activation function can help one get better results with even reduced data quality; hence, […].

Deep Learning 222

Deep Learning Data Quality Data Science Publishing 222

Smart Data Collective

DECEMBER 21, 2022

A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. The Global BPO Business Analytics Market was worth nearly $17 billion last year. Unfortunately, some business analytics strategies are poorly conceptualized.

Business Analytics 109

Business Analytics Analytics Data Quality Big Data 109

Smarten

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! When it comes to analytical quality versus analytical agility, we might see the issue in the same light. The information will be based on sophisticated analytics, but can be derived in minutes so users can make informed, fact-based decisions.

Data Quality 52

Data Quality Predictive Modeling Data-driven Visualization 52

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. Have I Checked The Raw Data And The Integrated Data?

Testing 124

Testing Metrics Data Quality Dashboards 124

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

David Menninger's Analyst Perspectives

MARCH 17, 2022

Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.

Business Intelligence 204

Business Intelligence Data Warehouse Data Quality Dashboards 204

Analytics Vidhya

DECEMBER 30, 2022

Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms. Almost all machine learning algorithms are data dependent, and […].

Machine Learning 282

Machine Learning Data Quality Data Science Publishing 282

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. What should be in that report about your data team? Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Alation

JUNE 9, 2023

We were thrilled to attend Gartner Data and Analytics Summit 2023 , on May 22–24 in London. D&A leaders from around the world gathered to discuss and find ways to overcome the latest challenges through strategies and innovations backed by data, analytics, and data science.

Data Analytics 52

Data Analytics Analytics Data Quality Data-driven 52

Smarten

MAY 13, 2022

When Considering Tally ERP Mobile Access, Add Augmented Analytics to Complete the Picture! Providing mobile access to Tally ERP allows users to leverage a familiar software solution to perform tasks and combines that access with new, value-added tools for augmented analytics.’. Users can track trends and perform analytics.

Analytics 76

Analytics Cost-Benefit Finance Data Quality 76

Sisense

APRIL 15, 2021

Analytics is the future. Your company is gathering data (and has likely been doing so for years), and you’ve probably got a system or two to glean insights from that data to make smarter decisions. The good news is that augmented analytics will make your life a lot easier! Simplify analytics with AI.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

TDAN

SEPTEMBER 5, 2023

Understanding your data may unearth hidden insights and move your business ahead, whether you’re a small startup or an established enterprise. However, going on the road of data analytics may […]

Data Analytics 128

Data Analytics Analytics Enterprise Data Quality 128

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 96

Analytics Insurance Big Data Uncertainty 96

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 311

Data Quality Metadata Data Governance Publishing 311

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 96

Data Governance Unstructured Data Metadata Data Lake 96

Smarten

DECEMBER 3, 2023

Let’s look at some of the reasons business intelligence (BI) and augmented analytics are important to your business and the benefits this type of solution can provide for your enterprise. Giving your team the right tools and a simple way to manage the overwhelming flow of data is crucial to business success.’

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 264

Machine Learning Data Quality Statistics Modeling 264

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. Data engineer job description.

Analytics 130

Analytics Data Science Statistics Unstructured Data 130

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 97

Analytics IT Data Lake Visualization 97

Alation

JUNE 2, 2022

In part two of this series, I’ll dive more deeply into AI/ML and data lineage, in the cloud and otherwise, and discuss how data governance and security can support these critical use cases, wherever they reside. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

DataKitchen

MARCH 12, 2024

After working with DataKitchen for a while, we noticed almost an absolute absence of data errors we didn’t catch earlier. Director, Data Analytics Team “We had some data issues. Data errors can cause compliance risks. Business users lose trust in the data and have an opportunity cost.

Metrics 117

Metrics Software Cost-Benefit Testing 117

Andrew White

FEBRUARY 10, 2020

Click here for an interactive PDF to connect to the most read data and analytics research directly. Melody Chien entered the charts last week at “number 6” and this week, her note ( Build a Data Quality Operating Model to Drive Data Quality Assurance ) was the most-read data and analytics note in our team.

Analytics 52

Analytics Data Quality Interactive Strategy 52

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

MAY 7, 2024

That’s according to a recent report based on a survey of CDOs by AWS in conjunction with the Chief Data Officer and Information Quality (CDOIQ) Symposium. The CDO position first gained momentum around 2008, to ensure data quality and transparency to comply with regulations following the housing credit crisis of that era.

Data Strategy 130

Data Strategy Data-driven Data Quality Strategy 130