DataKitchen

NOVEMBER 4, 2021

The typical pharmaceutical organization faces many challenges which slow down the data team: Raw, barely integrated data sets require engineers to perform manual , repetitive, error-prone work to create analyst-ready data sets. One data engineer called it the “last mile problem.” .

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

IBM Big Data Hub

MARCH 27, 2024

Some companies attempt to estimate Scope 3 emissions by collecting data from suppliers and manually categorizing data, but progress is hindered by challenges such as large supplier base, depth of supply chains, complex data collection processes and substantial resource requirements. This is where LLMs come into play.

Experimentation 82

Experimentation Modeling Deep Learning Data-driven 82

IBM Big Data Hub

FEBRUARY 2, 2024

A generative AI content engine fueled by trusted data This year’s solution uses watsonx to leverage a powerful large language model (LLM) hosted in the watsonx.ai But until now, content production had been highly manual and laborious. The solution: AI Stories with IBM watsonx.

Recreation/Entertainment 61

Recreation/Entertainment Broadcasting Consulting Dashboards 61

Cloudera

NOVEMBER 12, 2021

As a product manager, I rank features in my backlog against: How much revenue will this help me get? How hard is it for engineering to build? Simplicity on the other hand often argues that we need to “take features away”, undoing a lot of the things that were hard fought for earlier. What is the impact on my support costs?

Software 94

Software Enterprise Snapshot IT 94

DataKitchen

SEPTEMBER 20, 2021

Figure 2: The DataKitchen Platform helps you reduce time spent managing errors and executing manual processes from about half to 15%. The other 78% of their time is devoted to managing errors, manually executing production pipelines and other supporting activities. Manual Execution of Production. Source: DataKitchen.

Testing 246

Testing Metrics Measurement Dashboards 246

AWS Big Data

JUNE 6, 2023

For our customers, setting up these data quality checks is manual, time consuming, and error prone. It takes days for data engineers to identify and implement data quality rules. Data engineers must then write code to monitor data pipelines, visualize quality scores, and alert them when anomalies occur.

Data Quality 93

Data Quality Statistics Data Lake Visualization 93

IBM Big Data Hub

JANUARY 24, 2024

The test can be run manually or with automated tools through the lens of a specific course of action, or pen testing methodology. Open-Source Security Testing Methodology Manual Open-Source Security Testing Methodology Manual (OSSTMM) is one of the most popular standards of penetration testing.

Testing 81

Testing Risk Reporting IoT 81

DataKitchen

AUGUST 27, 2021

Arguably the most agile and effective data analytics capability in the pharmaceutical industry was accomplished cost-effectively, with a data engineering team of seven and another 10-12 data analysts. Perhaps more importantly, data engineers and scientists may change any part of the automated pipelines related to data at any time.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

IBM Big Data Hub

JULY 27, 2022

By replacing multiple manual IT operations tools with an intelligent, automated platform, AIOps enables IT operations teams to respond more quickly and proactively to slowdowns and outages, with less effort. The AIOps engine is focused on addressing four key things: Descriptive analytics to show what happened in an environment.

Prescriptive Analytics 93

Prescriptive Analytics Descriptive Analytics Data-driven Cost-Benefit 93

IBM Big Data Hub

AUGUST 8, 2023

The very features that make Kubernetes so attractive are also contributing to a complex and dynamic cloud infrastructure, leading to new cost drivers that demand careful attention and optimization strategies. Now available in the IBM Cloud catalog Sign up for a 30-day free trial of StormForge Optimize Live to get started.

Optimization 54

Optimization Cost-Benefit Machine Learning ROI 54

AWS Big Data

OCTOBER 3, 2023

But this approach requires you to implement the compaction job using your preferred job scheduler or manually triggering the compaction job. In this post, we discuss the new Iceberg feature that you can use to automatically compact small files while writing data into Iceberg tables using Spark on Amazon EMR or Amazon Athena.

Optimization 108

Optimization Snapshot Data Lake Metadata 108

IBM Big Data Hub

MAY 1, 2023

In this blog post, we will review the various methods of GCP cloud cost management, what problems they address and how GCP users can best use them. Migrate for Compute Engine is a GCP tool that has a right-sizing feature that recommends instance types for optimized cost and performance.

Optimization 88

Optimization ROI Consulting Dashboards 88

IBM Big Data Hub

AUGUST 22, 2023

It uses real-world data (both real time and historical) combined with engineering, simulation or machine learning (ML) models to enhance operations and support human decision-making. We can use this to scale the use of AI in identification of anomalies and damages on utility assets versus manually reviewing the image. Field services.

Unstructured Data 81

Unstructured Data Consulting Visualization IoT 81

IBM Big Data Hub

FEBRUARY 13, 2024

The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial. Invest in data hygiene and collection strategies to keep your engine running smoothly. Garbage in, garbage out.

Enterprise 126

Enterprise Modeling Testing Data-driven 126

DataKitchen

JANUARY 19, 2022

Beyond this initial use case, DataKitchen further extends Matillion workflows and pipelines with additional DataOps features and functions. DataKitchen uses this capability to automate analytics deployment from development to production, saving significant manual effort. Enterprises live in a multi-tool, multi-language world.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

Cloudera

AUGUST 10, 2021

you can look forward to new features, enhanced security, and better platform performance to help your business drive faster insights and value. Enhanced analytic features that deliver faster SQL queries and ETL with Hive on Tez and Impala, improved Spark with support for Spark 3.1 We expand on this feature later in this blog.

Metadata 97

Metadata Sales Statistics Management 97

Cloudera

OCTOBER 17, 2022

As we wrap up Hispanic Heritage month this #ClouderaLife Spotlight features Elias Avila, senior staff proactive support engineer for Cloudera. Elias Avila is a senior staff proactive support engineer who works directly with Cloudera’s customers. Working in Cloudera’s support organization.

Software 96

Software Optimization Management IT 96

Cloudera

MAY 9, 2022

It has been observed across several migrations from CDH distributions to CDP Private Cloud that Hive on Tez queries tend to perform slower compared to older execution engines like MR or Spark. This is usually caused by differences in out-of-the-box tuning behavior between the different execution engines. Default Value = 256 MB [i.e

Optimization 114

Optimization Testing Cost-Benefit Measurement 114

DataRobot Blog

MARCH 16, 2023

Traditionally, developing appropriate data science code and interpreting the results to solve a use-case is manually done by data scientists. An example of this is proposing why a feature has a high impact on predictions. Explaining results means translating what the raw data features represent and contextualizing the insight trends.

Data Science 98

Data Science Technology Data-driven Modeling 98

erwin

MARCH 5, 2020

Some (manual) reporting is possible. When engineers inspect the wind turbines, they record the results on paper forms. This manual, low-tech approach that relies on good penmanship equates to losing 10 days per year due to manual paperwork that delays necessary repairs; and work-order entry makes up about 25 percent of an admin’s day.

Digital Transformation 133

Digital Transformation Enterprise Management Modeling 133

AWS Big Data

NOVEMBER 28, 2023

ETL is the process data engineers use to combine data from different sources. Sunil Senan, SVP and Global Head of Data, Analytics, and AI, Infosys To learn more, see Aurora Docs , Amazon Redshift Docs , and the AWS News Blog. By automating complex ETL processes, data engineers can redirect their focus on creating value from the data.

Data Warehouse 90

Data Warehouse Data-driven Machine Learning B2B 90

Cloudera

SEPTEMBER 13, 2018

However, we’ll always need people to come up with the overarching prediction problems to solve and to make the ultimate choices to solve them, but there is a lot of data science work now that’s being done manually, and is repeated in project after project. Understanding the top features provides valuable insights into your business.

Machine Learning 40

Machine Learning Enterprise Data Science Risk 40

erwin

JANUARY 9, 2020

Then there’s unstructured data with no contextual framework to govern data flows across the enterprise not to mention time-consuming manual data preparation and limited views of data lineage. New Quick Compare templates as part of the Complete Compare feature to compare and synchronize data models and sources.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . The providers, having never contributed to the core functionality, often don’t have extensive engineering knowledge of the functionality. Watch this video to get an overview of CDW. .

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

datapine

NOVEMBER 5, 2019

The vast majority of business dashboards offer a customizable interface, a host of interactive features, and empower the user to extract real-time data from a broad spectrum of sources. Often times, statistical analysis is done manually and takes a lot of business hours to complete and provide recommendations for the future.

Dashboards 220

Dashboards Cost-Benefit Sales Metrics 220

AWS Big Data

OCTOBER 10, 2023

A lot of this effort is manual, where data owners and data stewards define and apply the policies statically up front for each dataset in the lake. Multiple personas consume data from the data lake, such as business leaders, data scientists, data analysts, and data engineers. The following diagram illustrates the solution architecture.

Data Quality 89

Data Quality Data Governance Data Lake Testing 89

Ontotext

JULY 13, 2023

Having search engines where it is difficult to find what you are looking for if you don’t search for the exact keyword Recommender systems that offer limited added value to the user. This blog gives an overview of a product bundling that relies on two industry leaders that help you do this.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

Cloudera

SEPTEMBER 9, 2021

Streamlined configuration: COD simplifies deployment of secure-by-default environments in an automated fashion, eliminating previously manual and error prone tasks such as configuring Kerberos for multiple clusters that required a lot of architectural decisions and scripting effort. Apache HBase, Store and Spark) etc.

Cost-Benefit 93

Cost-Benefit Optimization Risk Management 93

IBM Big Data Hub

NOVEMBER 21, 2023

OpenShift brings added-value features to complement Kubernetes, making it a turnkey container PaaS with a significantly improved developer and operator experience. The installation of ARO is scripted, and Red Hat site reliability engineers (SREs) are responsible for monitoring and maintaining the OCP cluster. x reaches end of life.

Cost-Benefit 51

Cost-Benefit Management Business Objectives Optimization 51

IBM Big Data Hub

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 72

Machine Learning Optimization Unstructured Data Sales 72

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. We used the existing Google BigQuery Connector for Glue following parts of this blog post. It was great for quick iteration over a new feature. She has been focusing on Digital Analytics and marketing data in the past.

Analytics 55

Analytics Data Lake Testing Optimization 55

Alation

SEPTEMBER 28, 2022

In addition, automated processes are often more accurate and reliable than manual processes, which leads to fewer errors and data that can be trusted. This requires that data engineers embrace learning and integrating new technologies, such as AI tools. Integrate Diverse Technologies. It’s a Team Sport.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Alation

AUGUST 30, 2022

Building on this great momentum, and especially customer success, we introduced the Alation Data Governance App, which includes key features like: Policy Center to centralize policy management, Workflows to automate actions like review and approvals, and. Read Q&A blog with Raj. Subscribe to Alation's Blog. In 2022.3,

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

IBM Big Data Hub

NOVEMBER 28, 2022

However, as data volumes continue to grow, manual approaches to metadata management are sub-optimal and can result in missed opportunities. You can enable advanced data discovery with AI-driven recommendation engines that analyze active metadata and recommend new assets to data consumers based on their usage patterns.

Metadata 57

Metadata Data Quality Data-driven Data Governance 57

Ontotext

MARCH 20, 2024

Keep your sales teams working in one primary tool: with the data sources integrated in one place, your sales team can become more productive by staying in SFDC rather than bouncing from tool to tool and performing data integration manually. Embark on your journey to data-driven success with the power of knowledge graphs and generative AI!

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Alation

SEPTEMBER 7, 2021

This is the last of the 4-part blog series. In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. Verifying quality is time consuming.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

DataRobot Blog

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52