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

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 112

Data Lake Analytics Dashboards Metrics 112

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration . Production Monitoring Only.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Then for knowledge transfer choose the repository, best suited for your organization, to host this information. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. public, private, hybrid cloud)?

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89