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

CIO Business Intelligence

JANUARY 19, 2024

Data scientist is one of the hottest jobs in IT. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects. The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Data Science 124

Data Science Machine Learning Predictive Modeling Experimentation 124

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. For example, imaging data can be used to show patients how an aligner will change their appearance over time. “It

Unstructured Data 100

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 100

Smart Data Collective

OCTOBER 20, 2021

The upsurge of data (with the introduction of non-traditional data sources like streaming data, machine logs, etc.) along with traditional ones challenge old models of data integration. Why is Data Integration a Challenge for Enterprises? This speeds up data transformation and decision-making.

Data Integration 122

Data Integration Machine Learning Big Data Data Transformation 122

datapine

SEPTEMBER 29, 2022

What Is Data Quality Management (DQM)? Data quality management is a set of practices that aim at maintaining a high quality of information. It goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Analytics Vidhya

MAY 13, 2024

Their ability to capture long-range dependencies and handle sequential data effectively has made them a staple in every AI researcher and practitioner’s toolbox.

Machine Learning 278

Machine Learning Analytics IT Forecasting 278

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 123

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 123

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. What does this mean for the Microsoft Data Platform Professional? Credit: [link].

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

CIO Business Intelligence

JANUARY 24, 2024

Unfortunately, the road to data strategy success is fraught with challenges, so CIOs and other technology leaders need to plan and execute carefully. Here are some data strategy mistakes IT leaders would be wise to avoid. Overlooking these data resources is a big mistake. Their large language models have poor or dirty data.

Data Strategy 133

Data Strategy Strategy Unstructured Data Data Governance 133

AWS Big Data

APRIL 11, 2023

With the proliferation of IoT devices and the abundance of data generated by them, it has become possible to collect real-time data on inventory levels, customer behavior, and other key metrics. Finally, we can use Amazon SageMaker to build forecasting models that can predict inventory demand and optimize stock levels.

Forecasting 76

Forecasting Management IoT Data-driven 76

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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 126

Data Analytics Diagnostic Analytics Management Analytics 126

FineReport

JUNE 7, 2024

By presenting data in visually appealing formats, decisions can be made promptly, leading to more efficient operations and strategic moves. Improving Business Insights Data visualization goes beyond just displaying numbers; it provides a deeper understanding of trends and patterns that might otherwise go unnoticed.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

AWS Big Data

APRIL 26, 2023

In 2019, the BMW Group decided to re-architect and move its on-premises data lake to the AWS Cloud to enable data-driven innovation while scaling with the dynamic needs of the organization. For historic reasons, the required data for this aggregation step is siloed and represented differently in diverse systems.

Forecasting 122

Forecasting Manufacturing Data Lake Big Data 122

IBM Big Data Hub

APRIL 14, 2023

However, their manual planning and budgeting process in spreadsheets posed several challenges, including lack of control, delayed data, poor execution, and the need for continuous follow-up with IT for actual data. They faced obstacles such as a prolonged budget process, manual forecasting, and no product profitability.

Forecasting 67

Forecasting Sales Dashboards Reporting 67

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 105

Data Warehouse Testing Data Quality Reporting 105

O'Reilly on Data

OCTOBER 19, 2021

Why: Data Makes It Different. Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. However, the concept is quite abstract. How can you start applying the stack in practice today?

IT 347

IT Testing Experimentation Software 347

BizAcuity

APRIL 1, 2023

But with a Power BI Premium license, you get to store BI assets on-premises and receive a 50 GB cap on dataset size and up to 100 TB data storage. So, you can choose to use Power BI Pro if you are a heavy business analytics user using it regularly for creating and consuming data using dashboards, data, and reports.

Optimization 52

Optimization Dashboards Sales Modeling 52

datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications. Did you know?

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

AWS Big Data

MARCH 16, 2023

This post is co-written by Anish Moorjani, Data Engineer at SafetyCulture. Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Data is made queryable in real time.

Metrics 89

Metrics Slice and Dice Data Warehouse Dashboards 89

BizAcuity

SEPTEMBER 21, 2022

But with a Power BI Premium license, you get to store BI assets on-premises and receive a 50 GB cap on dataset size and up to 100 TB data storage. So, you can choose to use Power BI Pro if you are a heavy business analytics user using it regularly for creating and consuming data using dashboards, data, and reports.

Optimization 52

Optimization Dashboards Sales Modeling 52

Cloudera

FEBRUARY 8, 2021

Development Environment for Data Scientists, Isolated, Containerized, and Elastic. Production ML Toolkit – Deploying, Serving, Monitoring, and Governance of ML models. Simple, drag-and-drop building of dashboards and apps with Cloudera Data Visualization. Now, let’s start testing our model! No, not really.

Machine Learning 77

Machine Learning Statistics Modeling Dashboards 77

Cloudera

OCTOBER 13, 2020

CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data. Predict – Data Engineering (Apache Spark). Enable Cloud Everywhere : Accelerate adoption of cloud-native data services for public clouds . New Services.

Data Warehouse 99

Data Warehouse Machine Learning Visualization Data Lake 99

IBM Big Data Hub

JULY 28, 2023

As an independent software vendor (ISV), we at Primeur embed the Open Liberty Java runtime in our flagship data integration platform, DATA ONE. For more than 35 years, we have been helping companies from all over the world to accelerate their data integration projects. Data Shaper , providing any-to-any data transformations.

Data Integration 55

Data Integration Optimization Software Insurance 55

Octopai

DECEMBER 11, 2022

Data compliance may be good tidings for consumers, customers and clients, but it’s a big pain in the neck for the organizations that need to comply. Let’s take a look at several regulatory standards and explore automated data lineage’s role in smoothing and improving data compliance. Can you find all that data?

Insurance 52

Insurance Risk Metadata Reporting 52

AWS Big Data

MARCH 13, 2024

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS. The ingestion approach is not in scope of this post.

Analytics 94

Analytics IoT Metadata Internet of Things 94

Ontotext

MARCH 20, 2024

Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility. As Dan Vesset, group vice president at IDC, stated, “People spend 60% to 80% of their time trying to find data. It’s a huge productivity loss.”

Data-driven 52

Data-driven Strategy Sales Data Integration 52

DataRobot Blog

MARCH 10, 2022

These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

CIO Business Intelligence

OCTOBER 18, 2022

The old stadium, which opened in 1992, provided the business operations team with data, but that data came from disparate sources, many of which were not consistently updated. The new Globe Life Field not only boasts a retractable roof, but it produces data in categories that didn’t even exist in 1992.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

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. Customers will now get the same consistent view of their data with the analytic processing engine of their choice without any compromises. . Fine grained access control (FGAC) with Spark.

Snapshot 92

Snapshot Cost-Benefit Machine Learning Data Transformation 92

Octopai

OCTOBER 6, 2022

We’re not sure if data assets experience stress when they have to migrate to a new residence, but certainly all of the humans involved in the data migration process do! A smart data mapping methodology starts with taking stock of your data assets and determining what really needs to come with you. What should stay behind?

Testing 52

Testing Visualization Data Transformation Strategy 52

DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires. Their product is the data.

Testing 152

Testing Dashboards Measurement Experimentation 152

Sisense

OCTOBER 15, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. Cleaning up dirty data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships. This makes LPGs inflexible.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Cloudera

DECEMBER 21, 2021

Packaging Apache Airflow and exposing it as a managed service within CDE alleviates the typical operational management overhead of security and uptime while providing data engineers a job management API to schedule and monitor multi-step pipelines. This also enables sharing other directories with full audit trails.

Snapshot 120

Snapshot Data-driven Optimization Management 120

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. Snowflake supports data that is structured, delimited (CSV, TSV, etc.)

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40