Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Altexsoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Big Data 59

Big Data Data Google Cloud Open Source 59

CIO

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Artificial Inteligence 298

Artificial Inteligence Data Artificial Intelligence Analytics 298

Altexsoft

APRIL 23, 2019

But how to turn unstructured data chunks into something useful? The answer is business intelligence. In this article, we will discuss the actual steps of bringing business intelligence into your existing corporate infrastructure. What is business intelligence? Data cleaning/standardization.

Business Intelligence 93

Business Intelligence Analytics Tools Strategy 93

CTOvision

SEPTEMBER 9, 2016

Zoomdata is the next generation data visualization system that easily allows companies and people to understand data visually in realtime. Zoomdata develops the world’s fastest visual analytics solution for big data. They are an In-Q-Tel company and a strategic investment in Zoomdata was announced on 8 Sep 2016.

Big Data 60

Big Data Data Analytics Scalability 60

CTOvision

MARCH 13, 2015

It has been in the business intelligence sector competing with capabilities from Business Objects, Microstrategy and Oracle. Here is info from the IBM website on capabilities: Performance and scalability with in-memory acceleration. Big data interoperability. By May Gourley. Flexible deployment.

Business Intelligence 89

Business Intelligence SOA Analytics Analysis 89

Perficient

NOVEMBER 17, 2024

This blog explores the key features of SAP Datasphere and Databricks, their complementary roles in modern data architectures, and the business value they deliver when integrated. SAP Datasphere is designed to simplify data landscapes by creating a business data fabric. What is SAP Datasphere?

Artificial Inteligence 59

Artificial Inteligence Machine Learning Architecture Analytics 59

CTOvision

AUGUST 1, 2015

“Organizations are spending billions of dollars to consolidate its data into massive data lakes for analytics and business intelligence without any true confidence applications will achieve a high degree of performance, availability and scalability. The post Immuta raises $1.5M

Big Data 114

Big Data System Data Software Engineering 114

AWS Machine Learning - AI

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI) -driven applications, the ability to efficiently process and analyze large datasets is a vital capability.

Serverless 106

Serverless AWS Artificial Inteligence Big Data 106

TechCrunch

FEBRUARY 7, 2022

Throughout the COVID-19 recovery era, location data is set to be a core ingredient for driving business intelligence and building sustainable consumer loyalty.

Business Intelligence 230

Business Intelligence AWS Data Engineering Sustainability 230

RapidValue

DECEMBER 7, 2020

With the addition of Oracle Analytics Cloud (OAC) , Oracle Cloud now has a PaaS solution that can manage all your data analytics requirements within one tool. It is a scalable, reliable, and secure cloud service with extensive analytics capabilities at a lower cost when compared to OBIEE. By, Dipin Manmadhan.

Business Intelligence 72

Business Intelligence Analytics Cloud How To 72

Altexsoft

FEBRUARY 8, 2021

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Perficient

MARCH 19, 2024

If you have built or are building a Data Lake on the Google Cloud Platform (GCP) and BigQuery you already know that BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.

Data 111

Data Google Cloud Analytics Serverless 111

CTOvision

MARCH 14, 2014

By Michael Johnson For enterprise technology decision-makers, functionality, interoperability, scalability security and agility are key factors in evaluating technologies. Pentaho has long been known for functionality, scalability, interoperability and agility. The introduction of Pentaho Business Analytics 5.0 Pentaho 5.0

Big Data 107

Big Data Business Analytics Analytics Company 107

Kaseya

NOVEMBER 9, 2023

Cloud infrastructure Four integral elements define the backbone of cloud infrastructure: Servers: Servers are the core of cloud infrastructure, acting as the computational engines that process and deliver data, applications and services. The servers ensure an efficient allocation of computing resources to support diverse user needs.

Cloud 105

Cloud Disaster Recovery Infrastructure Artificial Inteligence 105

Kentik

FEBRUARY 14, 2023

What are the main features of a modern data platform? Data platforms offer enterprises a range of features: Data ingestion Data storage Data transformation Data modeling Data discovery Data observability Data security Business intelligence Data platform ingestion Useful data is generated at every layer of an application.

Network 52

Network Data Artificial Inteligence Analysis 52

CIO

MARCH 24, 2023

Meant specifically to support self-service analytics, TrustCheck attaches guidelines and rules to data assets.

Government 357

Government Data Technical Review Policies 357

Perficient

JULY 4, 2023

The process involves extracting data from the source systems, transforming it into a format that can be used by the destination system, and then loading it into the destination system. This approach is often used when the destination system has the capability to perform complex transformations and data manipulation. What is ELT?

Big Data 52

Big Data Scalability Analysis Performance 52

Altexsoft

MARCH 18, 2021

From the late 1980s, when data warehouses came into view, and up to the mid-2000s, ETL was the main method used in creating data warehouses to support business intelligence (BI). As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Datavail

AUGUST 19, 2021

We’ve done a lot of research on this question, and we’ve compiled that research into a list of the most critical benefits organizations are looking for in terms of business intelligence (BI) systems that provide data analytics. Business leaders want the ability to do self-service data exploration and discovery.

Analytics 98

Analytics Data Business Intelligence Media 98

Datavail

JULY 7, 2022

Meanwhile, in an informal survey of attendees at a recent Datavail webinar, the majority (75 percent) of attendees said that their organization was pursuing a “hybrid” (partly on-premises and partly in the cloud) strategy for business intelligence and analytics. Agility and scalability. High data volumes.

Analytics 52

Analytics Artificial Inteligence Cloud Artificial Intelligence 52

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Perficient

FEBRUARY 28, 2023

So, they decided to invest in a secure and scalable cloud solution that would reduce maintenance costs, increase efficiency, and provide the data and analytics platform they needed to power their journey toward translational and personalized medicine.

Healthcare 64

Healthcare Technical Review AWS Analytics 64

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Coforge

JULY 28, 2021

Organizations can quickly solve these business challenges by embracing Azure Synapse Analytics, a limitless analytics service that brings together enterprise DWH and big data analytics. It enables companies to analyze data based on their standards through server-less, modern tools at scale.

Azure 52

Azure Analytics Data Artificial Intelligence 52

Xebia

JANUARY 19, 2023

. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink. – Jesse Anderson The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Altexsoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. Scalability. Scalability is one of Kafka’s key selling points.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Cloudera

NOVEMBER 19, 2020

Too often, though, legacy systems cannot deliver the needed speed and scalability to make these analytic defenses usable across disparate sources and systems. For many agencies, 80 percent of the work in support of anomaly detection and fraud prevention goes into routine tasks around data management. Fraudulent Activity Detection.

Government 118

Government Artificial Inteligence Data Machine Learning 118

Sunflower Lab

OCTOBER 2, 2023

Microsoft Azure’s Synapse Analytics is an integrated platform solution that brings together the capability of data warehousing, data connectors, ETL pipelines, analytics tools, and services, as well as the scale for big data, visualization, and dashboards.

Azure 40

Azure Analytics UI/UX Software Review 40

Hu's Place - HitachiVantara

JUNE 18, 2019

Scott Baker, posted a blog IDC: Object Storage More Than A One Trick Pony , which expanded on this IDC report and showed how our Object Storage platform, Hitachi Content Platform, HCP, evolved from a t rue archival compliance tool to one fine-tuned for Big Data analytics. However, simply migrating to any object store is not enough.

Storage 66

Storage Software Review Banking Technical Review 66

Kentik

JULY 10, 2018

Network data is big data. The collection of massive amounts of streaming telemetry requires a high-speed data pipeline for ingesting data in real time and distributing it to the appropriate monitoring and analytics tools.

Tools 45

Tools Cloud Big Data WAN 45

Cloudera

NOVEMBER 2, 2020

Correlations across data domains, even if they are not traditionally stored together (e.g. real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). The extreme scale of “big data”, but with the feel and semantics of “small data”.

Data 95

Data Analytics Storage Big Data 95

AWS Machine Learning - AI

AUGUST 8, 2024

RAG optimizes language model outputs by extending the models’ capabilities to specific domains or an organization’s internal data for tailored responses. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

Artificial Inteligence 111

Artificial Inteligence Data Generative AI AWS 111

Perficient

MARCH 14, 2023

As an AWS partner , we have extensive experience with Big Data , data warehousing , business intelligence , and analytics , and work with our clients to transform data into timely and actionable insights using AWS services such as AWS Glue, Amazon Redshift, Amazon Quicksight, and Athena.

Data 64

Data Healthcare AWS Analytics 64

CTOvision

OCTOBER 18, 2013

With the continuous development of advanced infrastructure based around Apache Hadoop there has been an incredible amount of innovation around enterprise “Big Data” technologies, including in the analytical tool space. H2O by 0xdata brings better algorithms to big data. Mike really nailed it with that one.

Technical Review 99

Technical Review Analytics Technology Big Data 99

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Altexsoft

DECEMBER 23, 2022

One of the main reasons behind this is the need to timely process huge volumes of data in any format. As said, ETL and ELT are two approaches to moving and manipulating data from various sources for business intelligence. In ETL, all the transformations are done before the data is loaded into a destination system.

Tools 52

Tools Software Review Systems Review Testing 52