Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale.

Technology 134

Technology Data Warehouse Big Data Machine Learning 134

BizAcuity

JULY 13, 2021

Optimize your Go To Market: The gaming business consists of various applications like the gaming platforms (Casino, Live Dealer, Poker, Sports, Bingo, etc.), account platform, payment, affiliate, loyalty system, bonus and promotion systems, financial application, CRM system, and many others. Data Enrichment/Data Warehouse Layer.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

IBM Big Data Hub

OCTOBER 1, 2018

The IBM Integrated Analytics System (IIAS), is a unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark.

Data Warehouse 72

Data Warehouse Machine Learning Big Data Optimization 72

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 94

Data Warehouse Data-driven Machine Learning B2B 94

Smart Data Collective

JUNE 7, 2019

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. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. What is Big Data? Cost and time reductions. Conclusion.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

Cloudera

OCTOBER 4, 2023

We can get to faster root-cause analysis and become proactive instead of reactive to changes in markets, business operations, and customer behavior. Making sure data is able to land in real time and be accessed just as fast requires a “best fit” partitioning scheme. Kudu has this covered. appeared first on Cloudera Blog.

Data Warehouse 84

Data Warehouse Experimentation Cost-Benefit Dashboards 84

Cloudera

JANUARY 19, 2022

Our position as a Visionary in the Gartner Magic Quadrant for Cloud DBMS market speaks to our product excellence and market-leading-vision of a hybrid, multifunction integrated platform with built-in security and governance. . We were named a Visionary having a strong market understanding and a robust roadmap for the cloud DBMS market.

Reporting 87

Reporting Data Warehouse Data Lake Machine Learning 87

Boris Evelson

JUNE 14, 2023

No matter what technology foundation you’re using – a data lake, a data warehouse, data fabric, data mesh, etc. – BI applications are where business users consume data and turn it into actionable insights and decisions. The BI market has […]

Business Intelligence 98

Business Intelligence Data Lake Data Warehouse Data-driven 98

CIO Business Intelligence

MARCH 28, 2022

After launching the Healthcare and Life Sciences Data Cloud Platform just a week ago, Snowflake has announced a Retail Data Cloud aimed at helping retail and consumer goods companies make the most of their data.

Consulting 107

Consulting Data Warehouse Machine Learning Dashboards 107

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 96

Management Data Warehouse Metrics Dashboards 96

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

CIO Business Intelligence

MAY 24, 2022

The new, industry-targeted data management platforms — Intelligent Data Management Cloud for Health and Life Sciences and the Intelligent Data Management Cloud for Financial Services — were announced at the company’s Informatica World conference Tuesday. Intelligent Data Management Cloud for Health and Life Sciences.

Finance 134

Finance Management Metadata Data Quality 134

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 113

Data Warehouse Cost-Benefit Sales Data-driven 113

CIO Business Intelligence

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

Machine Learning 135

Machine Learning Cost-Benefit Data-driven Strategy 135

Smart Data Collective

OCTOBER 27, 2021

The data is ever-increasing, and getting the deepest analytics about their business activities requires technical tools, analysts, and data scientists to explore and gain insight from large data sets. Interactive analytics applications make it easy to get and build reports from large unstructured data sets fast and at scale.

Interactive 113

Interactive Unstructured Data Analytics Data Warehouse 113

IBM Big Data Hub

OCTOBER 30, 2023

The global AI market is projected to grow to USD 190 billion by 2025, increasing at a compound annual growth rate (CAGR) of 36.62% from 2022, according to Markets and Markets. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

Insurance 87

Insurance Data Warehouse Data-driven Unstructured Data 87

Cloudera

JANUARY 20, 2021

Digital transformation is a hot topic for all markets and industries as it’s delivering value with explosive growth rates. Reporting – delivering business enterprise insight (sales analysis and forecasting, market research, budgeting as examples).

Digital Transformation 105

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 105

FineReport

MAY 6, 2020

Software Pemvisualisasi Data: excel, python, software profesional lainnya. Framework Big Data Processing: Hadoop, storm, spark. Data Warehous: SSIS, SSAS. Machine learning. Skill Data Mining: Matlab, R, Python. Seperti yang Anda ketahui, statistik adalah dasar analisis data. Data Warehouse.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

Smart Data Collective

NOVEMBER 18, 2020

Data Science is used in different areas of our life and can help companies to deal with the following situations: Using predictive analytics to prevent fraud Using machine learning to streamline marketing practices Using data analytics to create more effective actuarial processes. Where to Use Data Mining?

Data mining 143

Data mining Data Science Informatics Statistics 143

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Solution overview Amazon Forecast is a fully managed time series forecasting service based on machine learning.

Forecasting 83

Forecasting Data Warehouse Machine Learning Modeling 83

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 114

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 114

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 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

APRIL 3, 2024

You can share data for collaboration with one or more accounts in the same Snowflake region. You can also use data in Snowflake for visualization using Amazon QuickSight , or use it for machine learning (ML) and artificial intelligence (AI) purposes with Amazon SageMaker. Nidhi Gupta is a Sr.

Data Lake 95

Data Lake Snapshot Metadata Data Architecture 95

Sisense

APRIL 17, 2020

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. Data warehouses have changed the way the world deals with data. Why use a materialized view? and other more complex tasks.

Data Warehouse 90

Data Warehouse Visualization Statistics Machine Learning 90

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 132

Data mining Data-driven Statistics OLAP 132

CIO Business Intelligence

JUNE 23, 2023

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

Data Strategy 109

Data Strategy Strategy Visualization Consulting 109

Cloudera

JUNE 2, 2021

Data pipelines are in high demand in today’s data-driven organizations. As critical elements in supplying trusted, curated, and usable data for end-to-end analytic and machine learning workflows, the role of data pipelines is becoming indispensable.

Data Warehouse 89

Data Warehouse Machine Learning Data-driven Enterprise 89

Cloudera

DECEMBER 20, 2022

In that sense, access to the auction is more conservative and can lead to inefficiencies in the use of assets, as some of the energy produced may be discarded if it is not saleable in the intraday market. McKinsey estimates that the use of data-driven technologies can drive operating and maintenance cost savings of more than 12%.

Optimization 79

Optimization Data Analytics Analytics Cost-Benefit 79

CIO Business Intelligence

MAY 16, 2022

The advent of distributed workforces, smart devices, and internet-of-things (IoT) applications is creating a deluge of data generated and consumed outside of traditional centralized data warehouses. If we can take the data center with us, we can do all kinds of things that weren’t possible before,” Vilfort explains. “You

IoT 84

IoT Data Warehouse Internet of Things Machine Learning 84

CIO Business Intelligence

FEBRUARY 14, 2023

Investments in artificial intelligence are helping businesses to reduce costs, better serve customers, and gain competitive advantage in rapidly evolving markets. AI is the perception, synthesis, and inference of information by machines, to accomplish tasks that historically have required human intelligence.

Data Strategy 112

Data Strategy Strategy Machine Learning Data-driven 112

CIO Business Intelligence

MARCH 9, 2022

Data-driven organizations understand that data, when analyzed, is a strategic asset. It forms the basis for making informed decisions around product innovation, dynamic pricing, market expansion, and supply chain optimization. Cloudera and Dell Technologies for More Data Insights. It’s the “new oil.” The challenge: There.

Data-driven 93

Data-driven Analytics Machine Learning Optimization 93

Cloudera

OCTOBER 6, 2022

Reduce tech debt: Tech debt is a constant challenge — trying to move faster and deliver enhancements in a constantly evolving market is difficult. Optimize automation: AI and machine learning (ML) are now the key terms here, but RPA (Robotic Process Automation) still has its place in driving efficiency throughout the enterprise.

Digital Transformation 85

Digital Transformation Cost-Benefit Data Lake Machine Learning 85

CIO Business Intelligence

JUNE 21, 2023

We needed to transform ourselves … and grow faster than our competitors and faster than our markets required. The base engine for the e-commerce and data warehouse is all custom code. Machine learning was about comparing a lot of inputs. Surviving the pandemic wasn’t enough,” Peck adds. “We

IT 71

IT B2B Digital Transformation Sales 71

Jet Global

NOVEMBER 5, 2020

The company’s market power is based largely on its ability to promote the “stack”—that is, to position the entire suite of Microsoft products as a holistic solution to customer problems. OLAP reporting has traditionally relied on a data warehouse. Data lakes move that step to the end of the process.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If so, you know about the failed economics of some cloud-native solutions on the market today. Data warehouses have been broadly adopted to provide timely reports and valuable insights.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98