The Data Administration Newsletter

FEBRUARY 21, 2024

Explainable AI refers to ways of ensuring that the results and outputs of artificial intelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them.

Artificial Intelligence 52

Artificial Intelligence Data Modelling Data Governance Data Visualization 52

Smart Data Collective

MAY 29, 2023

The world of artificial intelligence (AI) is constantly changing, and we must be vigilant about the issue of bias in AI. Enabling external scrutiny requires developers’ accurate documentation of the training data, model architecture, and evaluation methodologies.

Artificial Intelligence 170

Artificial Intelligence Documentation Data Modelling Monitoring 170

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Enterprise Artificial Intelligence.

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Healthcare Big Data Data Governance 52

The BAWorld

MARCH 15, 2024

Thereby, learning visualization software such as Tableau can enhance your abilities as a data Analyst. This is the premier software used industry wide that enables you to display your analysis on dashboards, make data models, renderings and business intelligence reports.

Data Visualization 52

Data Visualization Artificial Intelligence Visualization Banking 52

Business Bullet

FEBRUARY 8, 2020

Cloud technology, big data and machine learning have grown in popularity and use and can be termed as disruptive technologies. There are now more projects based on data and being able to store more of it. Data modelling and analysis skills will be valuable as a result. Disruptive technologies.

Artificial Intelligence 52

Artificial Intelligence Business Analysis Business Analysis Digital Transformation 52

Astera

OCTOBER 7, 2022

Unstructured data do not have a pre-defined schema, so it cannot be stored in a traditional database until converted into a structured format. But unstructured data is no longer dark data, unavailable for analysis. It’s fair, given the unstructured data may hold valuable insights to augment a business’s market competitiveness.

Data Analytics 52

Data Analytics Data Analytics Documentation Customer Experience 52

Actian

MAY 21, 2019

For many years, companies have been accumulating large amounts of data with an intuitive feeling that it has value and would be put to good use to make more informed business decisions. The refinement process starts with the ingestion and aggregation of data from each of the source systems. Big-Data and Real-Time insights.

Big Data 40

Big Data Data Warehouse Artificial Intelligence Digital Transformation 40

Sisense

JUNE 12, 2019

our annual client conference, I gave a presentation that took a deep dive into artificial intelligence and subgroups including AI, ML, and statistics. Living in a World of Big Data. It all starts with the data. Yesterday, during Eureka! , If you were not in attendance at Eureka!

Artificial Intelligence 75

Artificial Intelligence Big Data Data Analytics Data Analytics 75

Sisense

APRIL 10, 2020

Nowadays text data is huge, so Deep Learning also comes into the picture. Deep learning works well with Big Data sets, and it is based on the concept of our brain cells (neurons), which is the root of the term “Artificial Neural Networks.” Both languages are user-friendly and easy to implement.

Visualization 98

Visualization Artificial Intelligence Data Mining Logistics 98

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Sisense

JULY 24, 2019

Last, and still a very painful challenge for most users, is the familiarity with the underlying data and data model. NLQ is gaining traction in the big data analytics tools domain for its quick answers and ease of use. In other words, how the variables are named, and the granularity of their values.

Skillset 89

Skillset Big Data Data Modelling Data Analytics 89

Data Pine

MARCH 31, 2022

A data scientist has a similar role as the BI analyst, however, they do different things. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis. They can help a company forecast demand, or anticipate fraud.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Sisense

FEBRUARY 24, 2021

Data space dimension: Traditional data vs. big data. This dimension focuses on what type of data the CDO has to wrangle. Traditional datasets are often relational data found at the core of transactional services and operations: Think of an accounting system or point-of-sale system that spans multiple locations.

Chief Data Officer 69

Chief Data Officer Data Warehouse Big Data Innovation 69

Whizlabs

APRIL 19, 2021

Currently she works at Microsoft and concentrates mainly on cloud computing, edge computing, distributed systems and architecture, and a little bit of machine learning and artificial intelligence. Navin is the founder of WoWExp , which transforms the Industry with Augmented Reality and Artificial Intelligence.

Cloud Computing 145

Cloud Computing IBM Support IBM Maintenance IBM cost 145

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Digital Transformation 98

Digital Transformation Data Warehouse IBM Support IBM cost 98

Astera

FEBRUARY 16, 2024

You can also schedule, monitor, and manage your data pipelines from a centralized dashboard, ensuring that Finance 360 pipelines are always up-to-date and reliable. You can access and ingest data from any source and system, regardless of the data’s location, format, or structure.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

Marutitech

DECEMBER 17, 2021

You must be wondering what the different predictive models are? What is predictive data modeling? This blog will help you answer these questions and understand the predictive analytics models and algorithms in detail. What is Predictive Data Modeling? Most Popular Predictive Analytics Techniques .

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

Smart Data Collective

OCTOBER 16, 2022

The advantages can be summed up as follows: Forced normalization and enrichment – In Open XDR, the system ensures that all data are similar or compatible with each other (normalized) before they are stored in a data lake. If the data is incomplete, additional information is sourced and appended (enrichment).

Data Security 338

Data Security Artificial Intelligence Cybersecurity Big Data 338

Insight Software

MAY 1, 2023

Ideally, your primary data source should belong in this group. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52