Smart Data Collective

JULY 20, 2021

Big data technology is incredibly important in modern business. One of the most important applications of big data is with building relationships with customers. These software tools rely on sophisticated big data algorithms and allow companies to boost their sales, business productivity and customer retention.

Sales 141

Sales Big Data Marketing Software 141

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 311

Management Data Warehouse Data Quality Data Integration 311

AWS Big Data

JUNE 29, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

Data Warehouse 58

Data Warehouse Dashboards Testing Visualization 58

IBM Big Data Hub

MARCH 11, 2019

Though the enterprise data warehouse (EDW) has traditionally been the repository for historical data such as sales and financials, it is quickly evolving to meet the demands of new technologies.

Data Warehouse 77

Data Warehouse Enterprise Sales Technology 77

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Smart Data Collective

MAY 31, 2022

Big data technology is having a huge impact on the state of modern business. The technology surrounding big data has evolved significantly in recent years, which means that smart businesses will have to take steps to keep up with it. What is Data Activation? It Started Reverse ETL.

Data Warehouse 133

Data Warehouse Big Data Data-driven Technology 133

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architect vs. data engineer The data architect and data engineer roles are closely related.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CDW Research Hub

MARCH 22, 2019

The solution helped make sense of an enormous amount of data about such things as member usage statistics, enrollment rates, contract and payment statuses, staffing and operations. empowering franchisees to use data for business decision-making, and. The integration of the Cognos environment with.

Data Warehouse 66

Data Warehouse Prescriptive Analytics Statistics Big Data 66

Smart Data Collective

JUNE 7, 2019

With today’s technology, there’s an increasing demand for stream processing. Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. Read this article as we’ll tackle what big data and stream processing are. What is Big Data?

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data Architecture 54

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 119

Data Warehouse Dashboards Risk Management Risk 119

Paul Blogs on BI

NOVEMBER 13, 2023

If the data is not correct then its garbage in and garbage out, or as I have always said : BIG DATA + BAD DATA = BIG BAD DATA However, when it comes to a good data strategy, it’s not just about the quality of the data, it’s also about the design and functionality of the structure where it is housed.

Data Strategy 52

Data Strategy Strategy Gap analysis Data Warehouse 52

bridgei2i

APRIL 21, 2021

He elaborates how ERP technology was adopted in the early 70s based on the computational power available at that time. The 2000s saw data warehouses being created and used as business intelligence picked up. The 2000s saw data warehouses being created and used as business intelligence picked up. Subscribe Now.

Forecasting 98

Forecasting Data Warehouse Manufacturing Machine Learning 98

Cloudera

DECEMBER 19, 2018

Natural language analytics and streaming data analytics are emerging technologies that will impact the market. Cloud computing has passed the tipping point, with most organizations comfortable moving critical data and applications to the public cloud. Big Data Technologies and Architectures.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. This may lead to misleading evaluations about the technology or concept being tested.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

Jen Stirrup

MAY 3, 2020

Azure Synapse is an Azure-based cloud analytics service that provides insights on all data across data warehouses and big data analytics systems. It combines familiar SQL technologies such as data warehousing with Spark technologies used in big data analytics.

Big Data 56

Big Data Data Warehouse Machine Learning Business Intelligence 56

Cloudera

FEBRUARY 7, 2019

With the right technology now in place, ATB Financial is landing and curating more data than ever to bring data-driven insights to the business and its customers. Implementing a Modern Data Architecture. ATB Financial is also the first to use SAS Viya to interface between SAS tools and HDP. Check out our customer stories.

Big Data 63

Big Data Data Analytics Analytics Data Architecture 63

Smart Data Collective

NOVEMBER 18, 2020

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. Where to Use Data Mining? Practical experience.

Data mining 143

Data mining Data Science Informatics Statistics 143

In(tegrate) the Clouds

DECEMBER 21, 2015

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. I can’t help it. Merv Adrian (@merv) December 19, 2015. platform.twitter.com/widgets.js.

Technology 45

Technology Internet of Things Digital Transformation Software 45

CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 108

Data Warehouse Cost-Benefit Sales Data-driven 108

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. As a result, organizations have spent untold money and time gathering and integrating data.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

OCTOBER 20, 2023

Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is passionate about architecting fast-growing data environments, diving deep into distributed big data software like Apache Spark, building reusable software artifacts for data lakes, and sharing knowledge in AWS Big Data blog posts.

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Azure Data Lakes are complicated.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

IBM Big Data Hub

NOVEMBER 3, 2023

Apache Kafka streams get data to where it needs to go, but these capabilities are not maximized when Apache Kafka is deployed in isolation. If you are using Apache Kafka today, Apache Flink should be a crucial piece of your technology stack to ensure you’re extracting what you need from your real-time data.

Cost-Benefit 78

Cost-Benefit Experimentation Testing Digital Transformation 78

Jen Stirrup

MAY 5, 2020

How can you differentiate the different opportunities to store your data in Azure? Now, it may not sound that interesting, but it’s crucial; if you don’t have your data, then you don’t have your business. So how do you choose which data source is right for your needs?

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 103

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 103

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. Real-world Business Solutions The real value of any technology is measured by its impact on real-world problems.

Insurance 89

Insurance Data Warehouse Data-driven Unstructured Data 89

AWS Big Data

MARCH 16, 2023

SafetyCulture is a global technology company that puts the power of continuous improvement into everyone’s hands. Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Refer to Getting started data sharing using the console for setup steps.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

IBM Big Data Hub

NOVEMBER 6, 2023

By adopting these 4 best practices to invest in the right technology and leverage the most recent advances in generative AI , enterprises can unlock unique services for SMB customers. Watsonx.data allows enterprises to centrally gather, categorize and filter data from multiple sources.

Cost-Benefit 116

Cost-Benefit Enterprise ROI Data Warehouse 116