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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

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.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration.

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How technology will define the future of UAE healthcare

CIO Business Intelligence

We are all familiar with the EMR (electronic medial records) adoption and maturity models designed by HIMSS (Healthcare Information and Management Systems Society). But honestly speaking, there exists no unique maturity model which measures the degree of digital transformation.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

Budget variance quantifies the discrepancy between budgeted and actual figures, enabling forecasters to make more accurate predictions regarding future costs and revenues. The Dupont analysis model comprises three key components: profit margin, asset turnover, and equity multiplier.

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Five Key Questions to Help Speed JD Edwards Financial Reporting

Jet Global

While JD Edwards transactional data is required to run period close reports, analyze trends, and prepare forecasts for planning and budgeting, it comes with a lot of complexity. JD Edwards World has no less than 1600 tables of data to support just its business applications. Each table can be huge.

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How a water technology company overcame massive data problems with ActionKPI and IBM

IBM Big Data Hub

Through the formation of this group, the Assessment Services division discovered multiple enterprise resource planning instances and payroll systems, a lack of standard reporting, and siloed budgeting and forecasting processes residing within a labyrinth of spreadsheets. It was chaotic.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

The response times for these data sources are critical to our key stakeholders. Therefore, we must take a data-driven approach to select a high-performance architecture. Storage and redundancy – Due to the heterogeneous data stores and models, it was challenging to store the different datasets from various business stakeholder teams.