DataKitchen

AUGUST 19, 2021

During the launch phase, the focus is on marketing to patients through consumer channels. As generic alternatives become available, the market enters the maturity phase where cost efficiency and margins become most important. There are different teams within the pharmaceutical company that focus on the respective target markets.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

IBM Big Data Hub

OCTOBER 1, 2018

It also runs on market-leading IBM Big Data Servers and IBM FlashSystem 900 storage arrays enabling a high-performance system optimized for business insight as well as advanced operational and in-database analytics.

Data Warehouse 72

Data Warehouse Machine Learning Big Data Optimization 72

Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. In financial services, fast-moving data is critical for real-time risk and threat assessments. Kudu has this covered. Ready to stop blinking and never miss a beat?

Data Warehouse 84

Data Warehouse Experimentation Cost-Benefit Dashboards 84

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. ExampleCorp has multiple Redshift clusters.

Management 97

Management Data Warehouse Metrics Dashboards 97

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. Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations.

Insurance 84

Insurance Data Warehouse Data-driven Unstructured Data 84

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

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 95

Data Warehouse Data-driven Machine Learning B2B 95

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 125

Consulting Data Warehouse Machine Learning Dashboards 125

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 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

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 114

Data Warehouse Cost-Benefit Sales Data-driven 114

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 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

Sisense

JULY 7, 2020

In-Warehouse Data Prep provides builders with the advanced functionality they need to rapidly transform and optimize raw data creating materialized views on cloud data warehouses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

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

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

IBM Big Data Hub

NOVEMBER 6, 2023

can analyze high-level customer trends and market forces — as well as specific customer data and historical transactions — to recommend products that meet each SMB’s particular needs. Data-driven personalization is essential in today’s business environment. Generative AI tools like IBM watsonx.ai

Cost-Benefit 109

Cost-Benefit Enterprise ROI Data Warehouse 109

Cloudera

JULY 21, 2022

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Cloudera Data Warehouse). Efficient batch data processing.

Metrics 83

Metrics Slice and Dice Data Warehouse Dashboards 83

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. It’s the “new oil.” The challenge: There.

Data-driven 110

Data-driven Analytics Machine Learning Optimization 110

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 144

Data mining Data-driven Statistics OLAP 144

Smart Data Collective

JULY 20, 2021

According to market research – The global CRM market size was estimated at USD 43.7 The current market is overpacked with several CRMs; hence, selecting the best CRM for business operations has become challenging for organizations. However, there are many CRMs in the online market, but nothing can beat Salesforce.

Sales 141

Sales Big Data Marketing Software 141

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

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

Sisense

AUGUST 4, 2021

AI-driven explanations will calculate and show the relative impact of the factors selected, giving users more control over their data and displaying correlations between different elements over time. Optimize your cloud data warehouse cost forecasting. Analytics adoption has stalled; only infused analytics can help.

Dashboards 52

Dashboards Analytics Data Warehouse Forecasting 52

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Cloudera

MARCH 2, 2022

You can read previous blog posts on Impala’s performance and querying techniques here – “ New Multithreading Model for Apache Impala ”, “ Keeping Small Queries Fast – Short query optimizations in Apache Impala ” and “ Faster Performance for Selective Queries ”. . Analytical SQL workloads use aggregates and joins heavily.

Data Warehouse 86

Data Warehouse Optimization Analytics Sales 86

Occam's Razor

APRIL 25, 2011

and meet many many many executives and hear about their digital marketing strategies, challenges and outcomes. This latter category contains things that are so obviously sub-optimal that no one should be doing them any more. But maybe the issue is that you (and the Marketers and Leaders. Yet there they are. We hate change.

Marketing 126

Marketing Measurement Metrics Testing 126

CIO Business Intelligence

JUNE 24, 2022

Because of these new-age companies, APAC has less legacy drag when compared to other mature markets such as North America. VSM calls for companies to adopt strategies to streamline and optimize the flow of value associated with business initiatives. Digital Transformation

Modeling 105

Modeling Digital Transformation Data Architecture Data-driven 105

Cloudera

JUNE 2, 2021

Often, these can be traced back to the weaknesses in the underlying data engineering solution architectures that have become archaic for modern data pipelines — posing a perennial problem for the data architects, data engineers, and data administrators.

Data Warehouse 89

Data Warehouse Machine Learning Data-driven Enterprise 89

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

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. The most common big data use case is data warehouse optimization.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

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. How edge refines data strategy.

IoT 98

IoT Data Warehouse Internet of Things Machine Learning 98

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

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Jedox

APRIL 8, 2021

Modern organizations of all types collect data. Traditional” data is being created in operational systems such as ERP, CRM, HCM and similar or related systems. Other sources of data may come from websites, marketing platforms, and market data. an approved budget).

Business Intelligence 89

Business Intelligence IT Forecasting Data Warehouse 89

BizAcuity

MAY 16, 2022

Data allowed Guinness to hold their market dominance for long. Now, businesses, regardless of the industry, are leveraging data and Business Intelligence to stay ahead of the competition. We get critical business insights based on how well we leverage our business data. Data mining. That was in the 1900’s.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78