Sisense

DECEMBER 11, 2019

The challenge is to do it right, and a crucial way to achieve it is with decisions based on data and analysis that drive measurable business results. This was the key learning from the Sisense event heralding the launch of Periscope Data in Tel Aviv, Israel — the beating heart of the startup nation. What VCs want from startups.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

AWS Big Data

SEPTEMBER 22, 2023

At Stitch Fix, we have been powered by data science since its foundation and rely on many modern data lake and data processing technologies. In our infrastructure, Apache Kafka has emerged as a powerful tool for managing event streams and facilitating real-time data processing.

Management 102

Management Metrics Cost-Benefit Data Lake 102

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 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

BizAcuity

MAY 10, 2022

2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. The platform is built on S3 and EC2 using a hosted Hadoop framework. An efficient big data management and storage solution that AWS quickly took advantage of.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Jet Global

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

bridgei2i

MARCH 3, 2021

Episode 4: Unlocking the Value of Enterprise AI with Data Engineering Capabilities. Unlocking the Value of Enterprise AI with Data Engineering Capabilities. They discuss how the data engineering team is instrumental in easing collaboration between analysts, data scientists and ML engineers to build enterprise AI solutions.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98

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. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

Cloudera

OCTOBER 25, 2022

The data lakehouse is gaining in popularity because it enables a single platform for all your enterprise data with the flexibility to run any analytic and machine learning (ML) use case. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

Cloudera

JANUARY 21, 2021

Cloudera’s Data Warehouse service allows raw data to be stored in the cloud storage of your choice (S3, ADLSg2). It will be stored in your own namespace, and not force you to move data into someone else’s proprietary file formats or hosted storage. Proprietary file formats mean no one else is invited in! Separate compute.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Andrew White

JANUARY 11, 2021

On January 4th I had the pleasure of hosting a webinar. It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. Coding skills – SQL, Python or application familiarity – ETL & visualization?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Cloudera

SEPTEMBER 6, 2022

Previously, there were three types of data structures in telco: . Entity data sets — i.e. marketing data lakes . It is an edge-to-AI suite of capabilities, including edge analytics, data staging, data quality control, data visualization tools, and machine learning.

Data Architecture 82

Data Architecture Cost-Benefit Digital Transformation Business Driver 82

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads.

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89