datapine

SEPTEMBER 29, 2022

However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way. Oftentimes, the data being collected and used is incomplete or damaged, leading to many other issues that can considerably harm the company. Enters data quality management.

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

NOVEMBER 10, 2023

Notification to Affected Parties: Once a problem is identified and the responsible party is notified, informing those impacted by the change is crucial. Implement a communication protocol that swiftly informs stakeholders, allowing them to brace for or address the potential impacts of the data change.

Data Quality 136

Data Quality Testing Data Lake Data Integration 136

Dataiku

SEPTEMBER 23, 2021

We speak a lot about the ways we can use data, transform it, and create powerful models based on advanced machine learning techniques, but we sometimes forget where the data comes from initially.

Machine Learning 103

Machine Learning Data Transformation Modeling IT 103

AWS Big Data

APRIL 26, 2023

The manufacturers need to know BMW Group’s exact current and future semiconductor volume information, which will effectively help steer the available worldwide supply. The data (Part Master Data) can directly be consumed from the Cloud Data Hub. The data (Part Master Data) can directly be consumed from the Cloud Data Hub.

Forecasting 124

Forecasting Manufacturing Data Lake Big Data 124

AWS Big Data

MAY 22, 2024

Amazon OpenSearch Ingestion is a fully managed serverless pipeline that allows you to ingest, filter, transform, enrich, and route data to an Amazon OpenSearch Service domain or Amazon OpenSearch Serverless collection.

Data Architecture 100

Data Architecture Visualization Data Transformation Management 100

Jet Global

MAY 6, 2024

Imagine this: sales data in your CRM uses opportunity IDs, while your ERP system uses unique sales order numbers. Merging these datasets requires not just combining the data, but also complex transformations to ensure corresponding fields like customer and product information align seamlessly.

Finance 52

Finance Reporting Data Transformation Optimization 52

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 91

Metadata Data Lake Visualization Data Transformation 91

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

CIO Business Intelligence

APRIL 30, 2024

This feature enables users to save calculations from a Tableau dashboard directly to Tableau’s metrics layer so they can monitor and track the information over time. It could tell the user whether the data is trending in a positive direction or what’s driving a trend, for instance. Metrics Bootstrapping.

Analytics 68

Analytics Metrics Visualization Dashboards 68

IBM Big Data Hub

NOVEMBER 20, 2023

Today’s healthcare providers use a wide variety of applications and data across a broad ecosystem of partners to manage their daily workflows. Integrating these applications and data is critical to their success, allowing them to deliver patient care efficiently and effectively. Is FHIR compatible with HL7?

Cost-Benefit 89

Cost-Benefit Data-driven Data Transformation Management 89

CIO Business Intelligence

FEBRUARY 20, 2024

The company can also unify its knowledge base and promote search and information use that better meets its needs. The data transformation imperative What Denso and other industry leaders realise is that for IT-OT convergence to be realised, and the benefits of AI unlocked, data transformation is vital.

Data Architecture 76

Data Architecture Unstructured Data Manufacturing IT 76

CIO Business Intelligence

JANUARY 24, 2024

Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake.

Data Strategy 131

Data Strategy Strategy Unstructured Data Data Governance 131

CIO Business Intelligence

AUGUST 3, 2023

But before consolidating the required data, Lenovo had to overcome concerns around sharing potentially sensitive information. Hoogar’s staff helped relieve such fears by educating employees that information included in the solution, such as notices of bug fixes or software updates, was already public.

Analytics 85

Analytics Data Lake Metadata Cost-Benefit 85

CIO Business Intelligence

FEBRUARY 16, 2023

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says.

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

datapine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? Proactivity: Another key benefit of big data in the logistics industry is that it encourages informed decision-making and proactivity.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. There’s also the issue of bias.

Data Warehouse 136

Data Warehouse Digital Transformation Data-driven Reporting 136

IBM Big Data Hub

JANUARY 9, 2024

ELT tools such as IBM® DataStage® facilitate fast and secure transformations through parallel processing engines. In 2023, the average enterprise receives hundreds of disparate data streams, making efficient and accurate data transformations crucial for traditional and new AI model development.

Enterprise 73

Enterprise Data Integration Data Quality Contextual Data 73

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

CIO Business Intelligence

MARCH 4, 2024

In an era of business where every industry requires its stakeholders to be capable of quick pivots and sharp turns, siloed information that ultimately slows decision-making can be the ultimate vulnerability. In this way, data may just be the ultimate disruptor – a fact that the insurance industry knows all too well.

Insurance 78

Insurance Strategy Data Governance Data Integration 78

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Data Virtualization allows accessing them from a single point, replicating them only when strictly necessary.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

APRIL 2, 2024

You can see the decompressed data has metadata information such as logGroup , logStream , and subscriptionFilters , and the actual data is included within the message field under logEvents (the following example shows an example of CloudTrail events in the CloudWatch Logs). You can connect with Ranjit on LinkedIn.

Metadata 88

Metadata Marketing Analytics Data Transformation 88

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

DataKitchen

JANUARY 23, 2023

Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. For example, if an error in the data causes a downstream system to fail, data lineage may not capture this information. They are performed on the data during production runtime when it is actively processed.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Smarten

MAY 13, 2024

To accomplish this interchange, the method uses data mining and machine learning and it contains components like a data dictionary to define the fields used by the model, and data transformation to map user data and make it easier for the system to mine that data. Simple interpretation of models in English.

Predictive Modeling 62

Predictive Modeling Data mining Modeling Predictive Analytics 62

DataKitchen

OCTOBER 25, 2022

The space agency created and still uses “mission control” where many screens share detailed data about all aspects of a space flight. That shared information is the basis for monitoring mission status, making decisions and changes, and then communicating to all people involved. DataOps Observability Starts with Data Journeys.

Testing 130

Testing Data-driven Visualization Dashboards 130

Smart Data Collective

OCTOBER 20, 2021

The data integration landscape is under a constant metamorphosis. In the current disruptive times, businesses depend heavily on information in real-time and data analysis techniques to make better business decisions, raising the bar for data integration. This speeds up data transformation and decision-making.

Data Integration 122

Data Integration Machine Learning Big Data Data Transformation 122

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. This allows your teams to make informed decisions based on real data, not just intuition.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

AWS Big Data

APRIL 11, 2023

With these AWS services, retailers can build an end-to-end inventory management and forecasting solution that provides real-time insights into inventory levels and customer behavior, enabling them to make informed decisions that drive business growth and customer satisfaction. The following diagram illustrates a sample architecture.

Forecasting 78

Forecasting Management IoT Data-driven 78

AWS Big Data

JUNE 20, 2023

You can perform log analysis on these logs to understand users’ application behavior and patterns to make informed decisions. Analyzing VPC flow logs helps you understand how your applications are communicating over the VPC network and acts as a main source of information to the network in your VPC. Choose Create delivery stream.

Dashboards 88

Dashboards Visualization Metrics Data Transformation 88

AWS Big Data

MAY 3, 2023

Components of the consumer application The consumer application comprises three main parts that work together to consume, transform, and load messages from Amazon MSK into a target database. The following diagram shows an example of data transformations in the handler component.

IoT 104

IoT Internet of Things Data Transformation Management 104

Alation

OCTOBER 18, 2022

Making this data visible in the data catalog will let data teams share their work, support re-use, and empower everyone to better understand and trust data. Data Transformation in the Modern Data Stack. Data engineering plays a critical role in distributing data to a wide audience.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. At the heart of this release is the need to empower people with the right information at the right time. With the launch of our latest product release, 2023.1,

Metadata 52

Metadata Cost-Benefit Data Transformation Predictive Modeling 52

Smarten

AUGUST 4, 2023

As your users become accustomed to augmented analytics, they will want the ability to quickly, and easily, gather data, integrated from disparate data sources. Users can then prepare that data – transforming, shaping, reducing, combining, exploring, cleaning, sampling, and aggregating data, to get the dataset users wish to analyze.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

AWS Big Data

NOVEMBER 15, 2023

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

Octopai

JUNE 22, 2023

In a self-service data management context, Octopai’s data lineage capabilities empower business users to navigate through complex data ecosystems. They can easily identify data sources, understand data transformations, and assess the impact of any changes they make.

Management 52

Management Data-driven Data Quality Data Governance 52

CDW Research Hub

JULY 23, 2021

Our fifth video will demonstrate data transformation and orchestration with Matillion into Snowflake. We will be performing some transformation and orchestration tasks within Matillion to accomplish our goal. These tasks include: Creating a transformation job for customer address and a table with extracted information.

Structured Data 52

Structured Data Consulting Strategy Data Strategy 52