CIO Business Intelligence

SEPTEMBER 14, 2022

technologies that fueled data strategies aimed at identifying inefficiencies, streamlining processes, and improving the ability to forecast and predict industry trends. Software engineer. Principal software engineer. Systems engineer. Sensors, AI, and robotics are key Manufacturing 4.0

Manufacturing 111

Manufacturing IT Software Digital Transformation 111

AWS Big Data

MARCH 29, 2024

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. With these insights, teams have the visibility to make data integration pipelines more efficient.

Metrics 103

Metrics Visualization Dashboards Interactive 103

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

OCTOBER 25, 2022

Part 2: Introducing Data Journeys. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.

Testing 130

Testing Data-driven Visualization Dashboards 130

DataKitchen

JANUARY 5, 2021

Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Data Science Workflow – Kubeflow, Python, R. Data Engineering Workflow – Airflow, ETL.

Testing 147

Testing Data Governance Metadata Visualization 147

AWS Big Data

APRIL 3, 2024

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Amazon DataZone now integrates directly with AWS Glue to display data quality scores for AWS Glue Data Catalog assets.

Data Quality 87

Data Quality Visualization Metadata Metrics 87

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? What should I track? Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

AWS Big Data

FEBRUARY 1, 2024

In general, you can build applications powered by LLMs by incorporating prompt engineering into your code. Prompt engineering is about guiding the model’s output by crafting input prompts, whereas fine-tuning is about training the model on custom datasets to make it better suited for specific tasks or domains.

Modeling 95

Modeling Metadata Data Processing Unstructured Data 95

Domino Data Lab

JULY 15, 2021

In the multiverse of data science, the tool options continue to expand and evolve. While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools. Snowflake ).

Data Science 145

Data Science Visualization Modeling Enterprise 145

AWS Big Data

MARCH 28, 2024

Krones equips their lines with sensors for data collection, which can then be evaluated against rules. Managed Service for Apache Flink manages the underlying Apache Flink components that provide durable application state, metrics, logs, and more, and Kinesis enables you to cost-effectively process streaming data at any scale.

Management 79

Management Broadcasting IoT Metrics 79

AWS Big Data

SEPTEMBER 7, 2023

Customers of all sizes and industries use Amazon Simple Storage Service (Amazon S3) to store data globally for a variety of use cases. Customers want to know how their data is being accessed, when it is being accessed, and who is accessing it. With exponential growth in data volume, centralized monitoring becomes challenging.

Metadata 98

Metadata Dashboards Metrics Visualization 98

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data. Query the data using Athena.

Snapshot 110

Snapshot Data Lake Metadata Recreation/Entertainment 110

datapine

MARCH 31, 2022

Does data excite, inspire, or even amaze you? Despite these findings, the undeniable value of intelligence for business, and the incredible demand for BI skills, there is a severe shortage of BI-based data professionals – with a shortfall of 1.5 2) Top 10 Necessary BI Skills. 3) What Are the First Steps To Getting Started?

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 101

Data Lake Management Metrics Data Warehouse 101

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Data Analytics 130

Data Analytics Diagnostic Analytics Management Analytics 130

DataKitchen

MAY 10, 2021

Data errors impact decision-making. Data errors infringe on work-life balance. Data errors also affect careers. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics.

Testing 214

Testing Manufacturing Data Quality Statistics 214

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Domino Data Lab

FEBRUARY 12, 2020

Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you. Ray: Scaling Python Applications.

Experimentation 137

Experimentation Modeling Data Science Management 137

AWS Big Data

JULY 28, 2023

Apache Flink and Apache Spark are both open-source, distributed data processing frameworks used widely for big data processing and analytics. Spark is known for its ease of use, high-level APIs, and the ability to process large amounts of data. Operations are supported in Scala, Java, Python, and R.

Data Processing 81

Data Processing Big Data Data Quality Technology 81

AWS Big Data

JUNE 5, 2023

By upgrading, you can take advantage of the latest capabilities of the Apache Airflow platform and maintain compatibility with new features and best practices like data-driven scheduling and new Amazon provider packages released in Apache Airflow 2.4.3. and above use Python v3.10, while older Apache Airflow versions use Python v3.7.

Snapshot 74

Snapshot Metadata Testing Data-driven 74

FineReport

DECEMBER 9, 2021

A business intelligence strategy is a framework that enables enterprises to use the right BI tools to analyze the correct data and then report to the right people to aid in making the right decisions. These goals include optimizing current business processes, creating top-notch products and services, and becoming a data-driven business.

Strategy 98

Strategy Business Intelligence KPI Key Performance Indicator 98

Sisense

MAY 27, 2019

That means there’s one Hell of a lot of data running through your organization. So, given the choice, which analytics job title should you choose: A data engineer or a data scientist? Digging Deep For Data Diamonds – The Data Engineer. Data’s like diamonds. That’s the job of the data engineer.

Statistics 75

Statistics Machine Learning Visualization Big Data 75

IBM Big Data Hub

AUGUST 11, 2023

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data. How the models are stored.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Exploratory Data Analysis After we connect to Snowflake, we can start our ML experiment.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

AWS Big Data

OCTOBER 5, 2023

Cost controls and usage tracking across these teams is also a critical factor. In the legacy big data and Hadoop clusters as well as Amazon EMR provisioned clusters, this problem was overcome by Yarn resource management and defining what were called Yarn queues for different workloads or teams.

Big Data 59

Big Data Cost-Benefit Testing Metrics 59

CIO Business Intelligence

JUNE 13, 2023

But now many are recognizing that data may be used in different ways and maybe access needs to be more regulated. The biggest worries are coming from websites that recognize how their data may be used to train AI models. Some are afraid that the models built from scraping their site will misuse or misunderstand the data.

IT 137

IT Scorecard Software Modeling 137

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks. Highlights.

Predictive Analytics 136

Predictive Analytics Analytics Statistics Machine Learning 136

CIO Business Intelligence

JUNE 28, 2022

Some call data the new oil. Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 134

Management Internet of Things Statistics Data-driven 134

AWS Big Data

MARCH 25, 2024

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

CIO Business Intelligence

MARCH 16, 2022

The pace of technology has evolved so rapidly over the last few years, multiplied by the pandemic, that it’s hard to keep track — and what’s most in demand today may be obsolete tomorrow. Identifying which emerging technologies will prove most useful is a challenge, though. Consider the constants.

Forecasting 94

Forecasting Machine Learning Technology Enterprise 94

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 81

Machine Learning Metrics Management Big Data 81

AWS Big Data

FEBRUARY 6, 2023

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that makes it simple to set up and operate end-to-end data pipelines in the cloud at scale. A data pipeline is a set of tasks and processes used to automate the movement and transformation of data between different systems.­

Management 83

Management Interactive Metadata Publishing 83

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. Composable ML then lets you add new types of feature engineering or build entirely new models. Run AutoPilot.

Machine Learning 52

Machine Learning Modeling Experimentation Visualization 52

AWS Big Data

NOVEMBER 9, 2023

Building a data platform involves various approaches, each with its unique blend of complexities and solutions. In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

AWS Big Data

APRIL 17, 2023

We have built data pipelines to process, aggregate, and clean our data for our forecasting service. With the growing interest in our services, we wanted to scale our batch-based data pipeline to process more historical data on a daily basis and yet remain performant, cost-efficient, and predictable.

Forecasting 78

Forecasting Cost-Benefit Optimization Testing 78

Sisense

OCTOBER 14, 2020

Here, we focus on the role of the data team in successfully applying advanced analytics and ensuring that you get the most from your data to make your organization truly data-driven. Smart organizations already appreciate the power of data and its influence on building successful strategies. Why build your data team?

Data-driven 98

Data-driven Machine Learning Dashboards Sales 98

DataRobot Blog

MARCH 10, 2022

By utilizing artificial intelligence, organizations can dissolve production bottlenecks, track and minimize/maximize critical KPIs like scrap rate and production rates, and get ahead of the power curve to accelerate their distribution and delivery channels. Time-Series Forecasting?—? Leveraging Snowflake and DataRobot for Speed and Scale.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52