Cloudera

OCTOBER 13, 2020

Data Warehouse – in addition to a number of performance optimizations, DW has added a number of new features for better scalability, monitoring and reliability to enable self-service access with security and performance . Enable Cloud Everywhere : Accelerate adoption of cloud-native data services for public clouds .

Data Warehouse 95

Data Warehouse Machine Learning Visualization Data Lake 95

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

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

Sisense

APRIL 10, 2020

In this article, we discuss how this data is accessed, an example environment and set-up to be used for data processing, sample lines of Python code to show the simplicity of data transformations using Pandas and how this simple architecture can enable you to unlock new insights from this data yourself.

Visualization 105

Visualization Reporting Data Processing Dashboards 105

Cloudera

FEBRUARY 8, 2021

Production ML Toolkit – Deploying, Serving, Monitoring, and Governance of ML models. Simple, drag-and-drop building of dashboards and apps with Cloudera Data Visualization. Stock Data – for pulling the stock data, I used alpha vantage service (free version). Now, let’s start testing our model!

Machine Learning 75

Machine Learning Statistics Modeling Dashboards 75

AWS Big Data

JULY 26, 2023

In this post, we assume the following three accounts: Pipeline account – This hosts the end-to-end pipeline Dev account – This hosts the integration pipeline in the development environment Prod account – This hosts the data integration pipeline in the production environment If you want, you can use the same account and the same Region for all three.

Data Integration 69

Data Integration Snapshot Testing Visualization 69

Sisense

OCTOBER 15, 2020

Upsolver encapsulates the streaming engineering complexity by empowering every technical user (data engineers, DBAs, analysts, scientists, developers) to ingest, discover, and prepare streaming data for analytics. The first step is to navigate to the “Data” tab and create a new live model. Now, let’s connect to Redshift.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

CIO Business Intelligence

OCTOBER 18, 2022

Noel had already established a relationship with consulting firm Resultant through a smaller data visualization project.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

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 90

Analytics IoT Metadata Internet of Things 90

DataKitchen

OCTOBER 5, 2021

The data organization wants to run the Value Pipeline as robustly as a six sigma factory, and it must be able to implement and deploy process improvements as rapidly as a Silicon Valley start-up. The data engineer builds data transformations. Their product is the data.

Testing 157

Testing Dashboards Measurement Experimentation 157

Sisense

MARCH 14, 2021

Before we dive into the topics of big data as a service and analytics applied to same, let’s quickly clarify data analytics using an oft-used application of analytics: Visualization! As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

APRIL 25, 2023

The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.

Sales 68

Sales Visualization Software Marketing 68

FineReport

MARCH 7, 2024

Data Analysis Report (by FineReport ) Note: All the data analysis reports in this article are created using the FineReport reporting tool. Leveraging the advanced enterprise-level web reporting tool capabilities of FineReport , we empower businesses to achieve genuine data transformation. Try FineReport Now 1.

Dashboards 52

Dashboards Reporting Advertising Statistics 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 60

Dashboards Testing Metrics Optimization 60

FineReport

APRIL 21, 2024

These solutions typically include data visualization, customizable dashboards, and self-service analytics. Tableau Tableau transforms data usage with end-to-end analytics, including data management, visual analytics, and storytelling. Features include interactive visualizations and native data connectors.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

DataKitchen

JULY 27, 2023

Azure Databricks, a big data analytics platform built on Apache Spark, performs the actual data transformations. The cleaned and transformed data can then be stored in Azure Blob Storage or moved to Azure Synapse Analytics for further analysis and reporting. Some tools are excellent for batch processing (e.g.,

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

O'Reilly on Data

JANUARY 17, 2023

Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? Building Models. A common task for a data scientist is to build a predictive model. You know the drill: pull some data, carve it up into features, feed it into one of scikit-learn’s various algorithms.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

AWS Big Data

MAY 9, 2023

AWS Glue Studio is a graphical interface that makes it easy to create, run, and monitor extract, transform, and load (ETL) jobs in AWS Glue. It allows you to visually compose data transformation workflows using nodes that represent different data handling steps, which later are converted automatically into code to run.

Visualization 71

Visualization Marketing Big Data IT 71

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

AWS Big Data

NOVEMBER 15, 2023

They can use their own toolsets or rely on provided blueprints to ingest the data from source systems. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization. The difference lies in when and where data transformation takes place.

Dashboards 91

Dashboards Analytics Metadata Data Warehouse 91

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Everything is visual. Azure Synapse Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

JANUARY 17, 2023

Great data science tools will assist data scientists and citizen data scientists in testing and training datasets for developing models, and ultimately for deploying them. 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 Business Intelligence 52

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 101

Management Metadata Analytics Dashboards 101

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 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 111

Management Cost-Benefit Data Transformation Optimization 111

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Jason: How do you use these models?

Metrics 52

Metrics Dashboards Sales Reporting 52

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. That data then fills several database tables.

Testing 130

Testing Data-driven Visualization Dashboards 130

Alation

JUNE 28, 2022

Collaborate more effectively: Break down data silos for better understanding of data assets across all business units. Create taxonomies and modeling languages: Enrich data analytics by enhancing relationships between data for ensuring consistent modeling outcomes when new data is introduced.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Peter James Thomas

MARCH 9, 2020

I last wrote about the process of creating a Data Strategy back in 2014 and – with the many changes that the field has seen since then – am overdue publishing an update, so watch this space. Such a model presents a series of states into which an organisation may fall with respect to its data.

Measurement 67

Measurement Strategy Data Strategy Modeling 67

Cloudera

OCTOBER 14, 2020

Also, such a concept helps admin to visualize the jobs which are scheduled for debugging purposes. Setting up the cluster to organization hierarchy based resource allocation model. For instance, Spark driver pods need to be scheduled earlier than worker pods. Lack of efficient capacity/quota management capability . Acknowledgments.

Machine Learning 116

Machine Learning Management Big Data Optimization 116

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

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. Business analysts use SageMaker Canvas to build ML models and generate predictions without needing to write code.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

Occam's Razor

OCTOBER 19, 2010

You simply cannot survive in this world with a clickstream mental model. I am forgetting the other 25 features these tools provide for free. I had promised tools and you got tools! Perhaps more than you cared for. But do remember three very very important things: 1. You have to embrace Web Analytics 2.0

Analytics 135

Analytics Testing Measurement Optimization 135

FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52