Pipeline Data Engineering

OCTOBER 15, 2021

The First Rule of Machine Learning: Start without Machine Learning Eugene Yan, Applied Scientist, Amazon Having robust data pipelines and high-quality data labels also suggests you’re ready for machine learning.

High Quality Data 52

High Quality Data Machine Learning Kafka Data Pipeline 52

Databand.ai

JULY 17, 2023

By adopting a set of best practices inspired by Agile methodologies, DevOps principles, and statistical process control techniques, DataOps helps organizations deliver high-quality data insights more efficiently. Learn more in our detailed guide to DataOps tools (coming soon) What Is MLOps?

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Monte Carlo

JANUARY 5, 2024

Innovations in data lakehouse architecture have been an important step toward more flexible and powerful data management systems. Data lakehouses, like Databricks’ Delta Lake , Amazon Redshift Spectrum , and now Snowflake for Data Lakehouse , help to unify data warehousing, machine learning, and analytics.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Innovations in data lakehouse architecture have been an important step toward more flexible and powerful data management systems. Data lakehouses, like Databricks’ Delta Lake , Amazon Redshift Spectrum , and now Snowflake for Data Lakehouse , help to unify data warehousing, machine learning, and analytics.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Precisely

JANUARY 22, 2024

But it’s critical to remember that when it comes to AI outputs, your results will only be as strong as the data that’s feeding them. Trusting your data is the cornerstone of successful AI and ML (machine learning) initiatives, and data integrity is the key that unlocks the fullest potential.

Data Integration 59

Data Integration High Quality Data Machine Learning Data Governance 59

RandomTrees

JANUARY 5, 2024

These techniques include machine learning (ML), knowledge graphs, rules, optimizations, and natural language processing. Testing and validation occur in controlled environments, where high-quality data gets used. What is Operationalizing AI?

Algorithm 52

Algorithm Business Analyst High Quality Data Portfolio 52

DataKitchen

FEBRUARY 18, 2022

Automation and orchestration in an interoperable hybrid cloud distributed data landscape is where DataOps excels. Whether an Artificial Intelligence, Machine Learning or Business Intelligence use case, all of them depend on governed, high-quality data delivered quickly.

High Quality Data 52

High Quality Data Business Intelligence Data Pipeline Government 52

Knowledge Hut

JANUARY 24, 2024

What Does a Data Scientist Do Data scientists are highly skilled professionals specializing in the art of extracting valuable insights from data. A significant part of their role revolves around collecting, cleaning, and manipulating data, as raw data is seldom pristine.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Enjoy a much more sophisticated computing environment than what’s available in a standard relational database – with data architectures based on tools like Databricks and Snowflake.

Data Integration 52

Data Integration High Quality Data BI Data 52

Picnic Engineering

DECEMBER 12, 2023

At Picnic, we track the latest machine learning developments to ensure the best possible demand forecasting. This blog post delves into the learnings and challenges on our journey towards implementing and scaling state-of-the-art deep learning approaches. For that use case a simple SQL query can be enough.

Machine Learning 52

Machine Learning Deep Learning Food High Quality Data 52

Cloudera

MAY 18, 2022

Address data management . No AI-first strategy can truly succeed without a well-defined data management strategy. After all, AI and it’s practice of machine learning (ML), use algorithms to accomplish tasks. Those algorithms require high quality data to deliver meaningful results.

Manufacturing 91

Manufacturing Retail High Quality Data Algorithm 91

Monte Carlo

JULY 27, 2023

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Ascend.io

FEBRUARY 28, 2024

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Snowflake

SEPTEMBER 27, 2023

To provide this level of care, healthcare professionals must manage complex health needs that require ongoing monitoring and treatment and must collaborate on data across care teams, facilities and systems.

Healthcare 82

Healthcare Accessible Accessibility Hospitality 82

Monte Carlo

JANUARY 10, 2024

On the other hand, “Can the marketing team easily segment the customer data for targeted communications?” usability) would be about extrinsic data quality. A data observability platform, like Monte Carlo’s, can help. It employs machine learning to empower data engineering teams to resolve data issues more rapidly.

Data Cleanse 52

Data Cleanse Data Engineering Data Engineer Engineering 52

U-Next

OCTOBER 27, 2022

Modern marketers are turning to Artificial Intelligence marketing strategies that use AI approaches and technologies such as data models, algorithms, and Machine Learning to optimize budgets, tailor content, and personalize the consumer experience. Machine Learning. Maintain High-Quality Data.

Designing 40

Designing Machine Learning Media Digital Media 40

AltexSoft

AUGUST 25, 2021

Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech. NLP techniques open tons of opportunities for human-machine interactions that we’ve been exploring for decades. Machine learning-based NLP — the basic way of doing NLP.

Process 139

Process Deep Learning Datasets Machine Learning 139

Databand.ai

JUNE 14, 2023

It enables: Enhanced decision-making: Accurate and reliable data allows businesses to make well-informed decisions, leading to increased revenue and improved operational efficiency. Risk mitigation: Data errors can result in expensive mistakes or even legal issues.

Amazon Web Services 52

Amazon Web Services Datasets High Quality Data ETL Tools 52

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It enables everything from reliable business logic to insightful decision-making and robust machine learning modeling. It is now the norm for tech companies to have a well-developed data platform.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Edureka

SEPTEMBER 11, 2023

Using this information, they generate synthetic data that follows the same rules, characteristics, or patterns as the training data, producing results that are novel and consistent with the original dataset in terms of their context and structure. For generative AI models to produce accurate results, high-quality data is necessary.

Algorithm 52

Algorithm Entertainment Healthcare Deep Learning 52

Data Engineering Podcast

APRIL 28, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Building 130

Building Data Lake High Quality Data Machine Learning 130

Knowledge Hut

JUNE 28, 2023

Goal Extracting valuable information from raw data for predictive or descriptive purposes. Methods and Techniques Machine learning, statistical analysis, clustering, classification, association rule mining, etc. Reporting, data visualization, online analytical processing (OLAP), ad hoc querying, etc.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

The Modern Data Company

DECEMBER 29, 2022

For example, using artificial intelligence and machine learning, banks can better protect customer identities across multiple channels while ensuring that sensitive customer data remains absolutely secure.

Banking 52

Banking Pipeline-centric Building Finance 52

Data Engineering Podcast

APRIL 21, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 182

Data Lake High Quality Data Data Pipeline Machine Learning 182

Monte Carlo

MAY 24, 2022

Before launching Monte Carlo, I spoke with hundreds of data leaders who all struggled to deliver high quality data despite having their teams spend upwards of 30% of their time and millions of dollars per year on this issue. Blinkist grew revenue by providing their marketing team with data to better optimize ad spend.

High Quality Data 52

High Quality Data Data Lake Media Data 52

Towards Data Science

JUNE 16, 2023

Data models on the critical path Data models are rarely critical on their own, but most often because of the importance of their downstream dependency, such as an important dashboard or a machine learning model used to serve recommendations to users on your website All data models upstream of a business-critical dashboard are on the critical path.

BI 82

BI Data ETL Tools Machine Learning 82

Monte Carlo

JUNE 16, 2023

Data quality has broad applications across industries, but its importance and degree of quality required is also contextual to the use case. For example, in marketing, high-quality data can help businesses better understand their customers, allowing them to create more targeted and effective campaigns.

Data Integration 52

Data Integration Hospitality Banking Healthcare 52

Databand.ai

JULY 5, 2023

Ensuring Data Quality Data accuracy is a critical factor in the success of any analytics or machine learning initiative. Low-quality data can result in incorrect insights and decision-making, ultimately impacting business outcomes.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

ProjectPro

JANUARY 31, 2023

Ever wondered how insurance companies successfully implement machine learning to expand their businesses? With the introduction of advanced machine learning algorithms , underwriters are bringing in more data for better risk management and providing premium pricing targeted to the customer.

Insurance 75

Insurance Machine Learning Project Algorithm 75

Data Engineering Podcast

FEBRUARY 18, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

MARCH 24, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 162

Data Lake High Quality Data Hadoop Data Pipeline 162

Monte Carlo

OCTOBER 11, 2022

We’ll then discuss how they can be avoided with an organizational commitment to high-quality data. Imagine this You’re a data scientist with a swagger working on a predictive model to optimize a fast-growing company’s digital marketing spend.

IT 52

IT Datasets Data Warehouse Data Analysis 52

AltexSoft

OCTOBER 13, 2022

Generative AI refers to unsupervised and semi-supervised machine learning algorithms that enable computers to use existing content like text, audio and video files, images, and even code to create new possible content. Discriminative modeling is used to classify existing data points (e.g., Let’s discuss each in more detail.

Algorithm 90

Algorithm Deep Learning Machine Learning Datasets 90

Monte Carlo

AUGUST 8, 2023

From this perspective, the data validation process looks a lot like any other DataOps process. This is because writing data validation tests is tedious and only provides coverage for a small subset of issues that can be anticipated. Without data lineage there is no way to tell. What’s next? We had a lot of dbt tests.

Data Validation 52

Data Validation Data Pipeline SQL Data 52

Cloudera

SEPTEMBER 20, 2022

A conscientious AI system designer should pay special attention to how they collect their data. To discuss this aspect in detail is beyond the scope of this document, but perhaps a good place to start is to explore alternatives to collecting large, high-quality data sets outside of scraping them from the internet.

Deep Learning 84

Deep Learning High Quality Data Telecommunication Systems 84

Data Engineering Podcast

APRIL 14, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Non-relational Database 147

Non-relational Database Relational Database Database Designing 147

Data Engineering Podcast

DECEMBER 24, 2023

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Kafka 245

Kafka Data Lake High Quality Data SQL 245