CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 136

Data Warehouse Digital Transformation Data-driven Reporting 136

AWS Big Data

NOVEMBER 9, 2023

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. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

datapine

SEPTEMBER 29, 2022

Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Sisense

AUGUST 6, 2020

Take Grammarly as an example: This popular program checks the grammar, tone, and style of documents. Getting this AI properly trained required a huge learning dataset with countless documents that were tagged according to specific criteria. Accurately prepared data is the base of AI. What will it take to build your MVP?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 63

Machine Learning Data Warehouse Modeling Cost-Benefit 63

AWS Big Data

JULY 25, 2023

Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what you use. Solution overview The integration of Talend with Amazon Redshift adds new features and capabilities.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Jet Global

MARCH 14, 2024

Mastering Data: Effectively Manage Your Data Download Now How Jet Analytics Enhances Microsoft Fabric Jet Analytics from insightsoftware is a complete data preparation, automation and modeling solution that enables Microsoft Dynamics customers to accelerate Dynamics ERP-ready BI projects without requiring specialist skills.

Analytics 52

Analytics Management Reporting Enterprise 52

Alation

JUNE 28, 2022

A metadata management framework combines organizational structure and a set of tools to create a data asset taxonomy. Document type: describes creation, storage, and use during business processes. Collaborate more effectively: Break down data silos for better understanding of data assets across all business units.

Metadata 52

Metadata Management Data Governance Machine Learning 52

DataRobot Blog

MARCH 10, 2022

By enabling data scientists to rapidly iterate through model development, validation, and deployment, DataRobot provides the tools to blitz through steps four and five of the machine learning lifecycle with AutoML and Auto Time-Series capabilities. Train, Compare, Rank, Validate, and Select Models for Production.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Data Transformation in the Modern Data Stack. Lineage between dbt sources, models, and metrics.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Cloudera

AUGUST 3, 2022

The challenges of arbitrary code execution notwithstanding, there have been attempts to provide a stronger security model but with mixed results. By leveraging Hive to apply Ranger FGAC, Spark obtains secure access to the data in a protected staging area. Learn more on how to use the feature from our public documentation. .

Snapshot 88

Snapshot Cost-Benefit Machine Learning Data Transformation 88

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Reporting 52

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Mapping a successful data migration can bring on rough weather.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 77

Data Governance Business Objectives Strategy Data Quality 77

Octopai

OCTOBER 6, 2022

Find some training datasets from an early ( too early) venture into AI modeling? Now that you’re feeling free as a bird without all that extraneous data (or heaving a sigh of nostalgia for a particularly sentimental dataset), it’s time to take all the keepers and start the data mapping process. One of those can go. Scrap them.

Testing 52

Testing Visualization Data Transformation Strategy 52

AWS Big Data

MARCH 13, 2024

You can modify the Lambda function to fetch additional vehicle information from a separate data store (for example, a DynamoDB table or a Customer Relationship Management system) to enrich the data, before storing the results in an S3 bucket. In this model, the Lambda function is invoked for each incoming event.

Analytics 97

Analytics IoT Metadata Internet of Things 97

Ontotext

DECEMBER 9, 2020

We all want to solve the interesting data challenges, build analytics, generate graph embeddings and train smart machine learning models over our knowledge graph data. This leads to lots of small data fetches to/from GraphDB over the network. Custom code also tends to over-fetch data that is not required.

Modeling 130

Modeling Management Optimization Metrics 130

Alation

JANUARY 17, 2023

As data science is growing in popularity and importance , if your organization uses data science, you’ll need to pay more attention to picking the right tools for this. An example of a data science tool is Dataiku. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

APRIL 19, 2023

This allows for a new way of thinking and new organizational elements—namely, a modern data community. However, today’s data mesh platform contains largely independent data products. Even with well-documented data products, knowing how to connect or join data products is a time-consuming job.

Technology 85

Technology Data-driven Machine Learning Sales 85

Alation

NOVEMBER 22, 2022

It’s not uncommon for analysts to struggle to access mission-critical data – even if they need it for urgent projects. This is why public agencies are increasingly turning to an active governance model, which promotes data visibility alongside in-workflow guidance to ensure secure, compliant usage. Standardizing data formats.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

AWS Big Data

FEBRUARY 26, 2024

When you start the process of designing your data model for Amazon Keyspaces, it’s essential to possess a comprehensive understanding of your access patterns, similar to the approach used in other NoSQL databases. Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery.

Dashboards 64

Dashboards Testing Metrics Optimization 64

bridgei2i

SEPTEMBER 3, 2020

Ronobijay: Sure, I think it would, you know, what used to be anathema till a few months back, you know, data transformation is real now, right? We would have to visit a branch possibly, you know, multiple locations, submit multiple documents. So earlier customers would spend a week or two, trying to open a bank account.

Enterprise 94

Enterprise Insurance Digital Transformation Interactive 94

Ontotext

APRIL 4, 2019

We translate their documents, presentations, tables, etc. Milena Yankova : We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it. Milena Yankova : We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

AWS Big Data

MARCH 3, 2023

Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

Jet Global

NOVEMBER 7, 2023

A complete data warehouse—without the heavy lifting: Automate the entire data warehousing process, from data retrieval through data transformation to deployment and generation of project documentation.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. Feature Engineering Terminology and Motivation.

Testing 68

Testing Modeling Interactive Measurement 68

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52