IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. The dedicated data analyst Virtually any stakeholder of any discipline can analyze data.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Cloudera

JANUARY 13, 2021

Putting data at the heart of the organisation. To drive the vision of becoming a data-enabled organisation, UOB developed the EDAG (Enterprise Data Architecture and Governance) platform. The platform is built on a data lake that centralises data in UOB business units across the organisation.

Digital Transformation 56

Digital Transformation Data-driven Data Lake Big Data 56

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Peter James Thomas

APRIL 9, 2019

These are as follows: General Data Articles. Data Visualisation. Statistics & Data Science. Analytics & Big Data. Many companies want to become data driven, but getting started on the journey towards this goal can be tough. Analytics & Big Data. CDO perspectives.

Data-driven 49

Data-driven Statistics Data Science Big Data 49

Peter James Thomas

MAY 3, 2019

Data Architecture / Infrastructure. When I first started focussing on the data arena, Data Warehouses were state of the art. More recently Big Data architectures, including things like Data Lakes , have appeared and – at least in some cases – begun to add significant value.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

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 87

Data Warehouse Sales Visualization Data Processing 87

CIO Business Intelligence

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

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. The era of big data has arrived.

Modeling 52

Modeling OLAP Reporting Sales 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

FineReport

MARCH 24, 2024

Python: Known for its text data handling capabilities and compatibility with various platforms and databases. Excel: Widely used for preliminary data analysis and modeling, featuring advanced business analytics options. During data analysis, professionals utilize an array of tools for accuracy and efficiency.

Statistics 52

Statistics Data mining Visualization Reporting 52

Sisense

APRIL 26, 2020

Cloud data warehouses: The new era of data storage. Cloud data warehouses aggregate data from different sources into a central, consistent data store to support various business, analytics, visualization, AI, and ML purposes.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

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. Especially for all Business Analytics professionals out there (2009). [7].

Statistics 49

Statistics Metrics Data Quality Measurement 49

Smart Data Collective

AUGUST 7, 2019

Big data has the power to transform any small business. However, many small businesses don’t know how to utilize it. One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today.

Data Analytics 111

Data Analytics Analytics Big Data Advertising 111

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52