Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This is the essence of Convergent Evolution.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

IBM Big Data Hub

SEPTEMBER 19, 2023

Data scientists also rely on data analytics to understand datasets and develop algorithms and machine learning models that benefit research or improve business performance. The dedicated data analyst Virtually any stakeholder of any discipline can analyze data.

Data Science 79

Data Science Data Analytics Prescriptive Analytics Analytics 79

FineReport

MARCH 24, 2024

They utilize specialized tools to gather data from diverse sources and organize it for visualization in reports and presentations. BI tools : Enables data aggregation, analysis, and visualization through dashboards and shared reports. Jupyter Notebooks: Simplifies code testing and collaboration for data analysis tasks.

Statistics 52

Statistics Data mining Visualization Reporting 52

Smart Data Collective

AUGUST 7, 2019

New England College talks in detail about the role of big data in the field of business. They have highlighted some of the biggest applications, as well as some of the precautions businesses need to take, such as navigating the death of data lakes and understanding the role of the GDPR. Customer data platform.

Data Analytics 100

Data Analytics Analytics Big Data Data Lake 100

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 83

Data Warehouse Sales Visualization Data Processing 83

Jet Global

OCTOBER 22, 2020

The world of business analytics is evolving rapidly. The size and scope of business databases have grown as ERP functionality has evolved, businesses have increased their adoption of CRM and marketing automation, and collaboration networks have become more common. That means tabular models need to be revisited.

Modeling 52

Modeling OLAP Reporting Sales 52

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Your Chance: Want to put your big data knowledge to use?

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Jet Global

JUNE 13, 2022

When migrating to the cloud, there are a variety of different approaches you can take to maintain your data strategy. Those options include: Data lake or Azure Data Lake Services (ADLS) is Microsoft’s new data solution, which provides unstructured date analytics through AI. Interested in Power BI.

Reporting 52

Reporting Data Lake Sales Operational Reporting 52

Peter James Thomas

MAY 3, 2019

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. When I first started focussing on the data arena, Data Warehouses were state of the art. I will start at the top left and work across and then down.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Jet Global

SEPTEMBER 19, 2023

What are the best practices for analyzing cloud ERP data? How can we respond in real time to the company’s analytic needs? Data Management How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP?

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Enterprise 52

Jet Global

SEPTEMBER 30, 2022

What are the best practices for analyzing cloud ERP data? How can we respond in real time to the company’s analytic needs? Data Management. How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP? Self-service BI.

Reporting 52

Reporting Data Warehouse Operational Reporting Enterprise 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Age maybe against us.

Analytics 68

Analytics Metadata Data Governance Management 68

Peter James Thomas

AUGUST 12, 2018

In our modern architectures, replete with web-services, APIs, cloud-based components and the quasi-instantaneous transmission of new transactions, it is perhaps not surprising that occasionally some data gets lost in translation [5] along the way. Regular facts are subject to data quality issues, or manipulation by creative humans.

Metrics 49

Metrics Statistics Data Quality Measurement 49