AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Maintaining lists of possible values for the columns requires continuous updates.

Metadata 94

Metadata Data Lake Modeling Data Warehouse 94

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 105

Data Warehouse KPI Optimization Cost-Benefit 105

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

Data Warehouse 122

Data Warehouse Testing Data Quality Reporting 122

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. It’s a fluid situation.”

Analytics 130

Analytics Machine Learning Data mining Software 130

CIO Business Intelligence

FEBRUARY 16, 2023

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

SEPTEMBER 6, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. You can also schedule stored procedures to automate data processing on Amazon Redshift. Satesh Sonti is a Sr.

Data Warehouse 112

Data Warehouse Insurance Statistics Software 112

datapine

SEPTEMBER 29, 2022

Paired to this, it can also: Improved decision-making process: From customer relationship management, to supply chain management , to enterprise resource planning, the benefits of effective DQM can have a ripple impact on an organization’s performance. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Cloudera

APRIL 12, 2021

The United States Veterans Administration (VA) over the last decade underwent a massive enterprise-wide IT transformation, eliminating its fragmented shadow IT and adopting a centralized system capable of supporting the agency’s 400,000 employees and more effectively utilizing its $240 billion-plus annual budget.

Enterprise 53

Enterprise IT Digital Transformation Data Warehouse 53

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

CIO Business Intelligence

JANUARY 9, 2023

Customers are increasingly demanding access to real-time data, and freight transportation provider Estes Express Lines is among the rising tide of enterprises overhauling their data operations to deliver it. While the company had a data warehouse, it was primarily used for analysis.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

AWS Big Data

AUGUST 13, 2024

We will create a glue studio job, add events and venue data from the SFTP server, carry out data transformations and load transformed data to s3. Seun has a background in analytics, data engineering which he uses to help customers achieve their outcomes and goals. Select Visual ETL in the central pane.

Data Processing 104

Data Processing Visualization Data Lake Data Processing 104

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

IBM Big Data Hub

OCTOBER 16, 2023

In other words, instead of training numerous models on labeled, task-specific data, it’s now possible to pre-train one big model built on a transformer and then, with additional fine-tuning, reuse it as needed. They offer an enterprise-ready dataset with trusted data that’s undergone negative and positive curation.

Risk 70

Risk Modeling Management Metadata 70

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.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

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 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Insight

APRIL 8, 2020

Data architects and data modelers who specialize in areas such as schema design, identifying query access patterns and building and maintaining data warehouses. The problem requires use of one or two foundational data structures and details some sort of analysis that we’d like performed on a dataset.

Data Warehouse 96

Data Warehouse Cost-Benefit Software Optimization 96

Sisense

MAY 11, 2021

Here at Sisense, we think about this flow in five linear layers: Raw This is our data in its raw form within a data warehouse. We follow an ELT ( E xtract, L oad, T ransform) practice, as opposed to ETL, in which we opt to transform the data in the warehouse in the stages that follow.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. 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

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 111

Data Lake Snapshot Big Data Data-driven 111

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 82

Reporting Metrics Optimization Data Lake 82

FineReport

APRIL 21, 2024

Features include interactive visualizations and native data connectors. FineReport FineReport, a versatile reporting tool designed for creating, analyzing, and presenting reports, facilitates the effortless construction of dynamic data analysis and reporting systems. Considering these factors, FineReport may be your best choice.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. The Amazon S3 sink connector further streams data into Amazon S3 in real time by partitioning data into fixed-sized files. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

Rocket-Powered Data Science

MARCH 20, 2023

We could further refine our opening statement to say that our business users are too often in a state of being data-rich, but insights-poor, and content-hungry. This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.”

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

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 119

Data Lake Management Metrics Data Warehouse 119

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

AWS Big Data

DECEMBER 4, 2024

Under the federated mesh architecture, each divisional mesh functions as a node within the broader enterprise data mesh, maintaining a degree of autonomy in managing its data products. This model balances node or domain-level autonomy with enterprise-level oversight, creating a scalable and consistent framework across ANZ.

Metadata 98

Metadata Data Governance Data Quality Data-driven 98

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. The result is a lower total cost of ownership and trusted data and analytics.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

CIO Business Intelligence

AUGUST 3, 2023

And at First Commerce Bank, EVP and COO Gregory Garcia hopes to leverage unified, real-time data to monitor risks such as worsening vacancy rates that could make it harder for commercial property owners to pay their mortgages. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

CIO Business Intelligence

NOVEMBER 7, 2023

In fact, as companies undertake digital transformations , usually the data transformation comes first, and doing so often begins with breaking down data — and political — silos in various corners of the enterprise. Some of this data might previously have been accessible to only a small number of groups or users.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142