CTOvision

JULY 31, 2013

By Ryan Kamauff Peter Schlampp, the Vice President of Products and Business Development at Platfora, explains what the Hadoop Big Data reservoir is and is not in this webinar that I watched today. Knowing what the HDR is and is not is key to pulling out business intelligence insights and analytics.

Big Data 91

Big Data Data Business Intelligence Analytics 91

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

CIO

JANUARY 20, 2023

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions.

Business Intelligence 360

Business Intelligence Data Business Analytics Analytics 360

The Accidental Successful CIO

JUNE 26, 2013

One of the things that makes having the CIO job different today from how it was in the past, besides the growing awareness of the importance of information technology, is the arrival of so-called “big data” We’re talking about terabytes or even petabytes of data and all of the headaches that come along with it.

Big Data 74

Big Data Data Analytics Innovation 74

CIO

MARCH 24, 2023

A framework for managing data 10 master data management certifications that will pay off Big Data, Data and Information Security, Data Integration, Data Management, Data Mining, Data Science, IT Governance, IT Governance Frameworks, Master Data Management

Government 357

Government Data Technical Review Policies 357

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

Perficient

FEBRUARY 16, 2023

The Data Catalog serves as an inventory of available data and provides information to evaluate the usefulness and quality of data to answer business questions and make better business decisions.

Data 110

Data Google Cloud Analytics Cloud 110

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Big Data is Not Just More Data : That’s because the nature of the data we can now collect has changed.

Big Data 33

Big Data Data Storage Journal 33

Kentik

JULY 18, 2016

Seeing Beneath the Surface with Post-Hadoop Big Data. At Kentik, we believe deeply in the power of post-Hadoop Big Data to address those limitations, making rich data readily accessible not only to engineering and operations, but also to wider areas of the organization. Dig deep without a backhoe.

Big Data 40

Big Data Network Analytics Data 40

Strategy Driven

APRIL 29, 2023

Use Big Data Analytics (BDA) Big data analytics (BDA) involves analyzing large and complex data sets to gain insights and make data-driven decisions. BDA can help companies identify patterns and trends in their data, providing valuable insights into their prospects.

Data 38

Data Weak Development Team Real Estate Storage 38

CTOvision

FEBRUARY 4, 2015

If you are into technology and government and want to find ways to enhance your ability to serve big missions you need to be at this event, 25 Feb at the Hilton McLean Tysons Corner. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 134

Fractional CTO Technical Review Big Data Analytics 134

Apps Associates

MAY 18, 2021

Performing analytics on the data was possible but took a long time and was mostly done in batch (using map reduce routines written in Java). Although on-premises Hadoop clusters ushered in the era of Big Data and supported data use cases that previously were not possible, many of these systems proved to be costly and cumbersome to maintain.

Cloud 98

Cloud Data Azure Analytics 98

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

CTOvision

JANUARY 18, 2015

This popular gathering is designed to enable dialogue about business and technical strategies to leverage today’s big data platforms and applications to your advantage. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

Openxcell

JANUARY 6, 2023

Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. Cloud storage functions by allowing users to access and download data on any selected device, such as a laptop, tablet, or smartphone, via an Internet service connection.

Architecture 52

Architecture Cloud Storage Google Cloud 52

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. High data volumes.

Analytics 52

Analytics Artificial Inteligence Cloud 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

Perficient

FEBRUARY 28, 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.

Healthcare 64

Healthcare Technical Review AWS Analytics 64

KitelyTech

AUGUST 13, 2023

Working with big data is a challenge that every company needs to overcome to see long-term success in increasingly tough markets. Dealing with big data isn’t just one issue, though. It is dealing with a series of challenges relating to everything from how to acquire data to what to do with data and even data security.

Big Data 52

Big Data Data How To Analytics 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Today, the Hive metastore is used from multiple engines and with multiple storage options.

Data 89

Data Analytics Open Source Architecture 89

Apiumhub

APRIL 22, 2021

Data modeling tools become critical here because they enable organizations to make data-driven decisions and meet varied business goals. What is Data Modeling? Data modeling is the process of visualizing and representing data for storage in a data warehouse. Key Data modeling tools.

Tools 59

Tools Data Business Intelligence Analytics 59

Kentik

JANUARY 19, 2016

Network data is a source of truth for everything in the modern business. Network data not only provides insight into the health and performance of IT infrastructure; it can also provide business intelligence. Enterprises are crunching flow records with big data.

Network 40

Network Cloud Data Big Data 40

Apiumhub

MARCH 16, 2021

With more and more data available, it’s getting more difficult to focus on the information we really need and present it in an actionable way and that’s what business intelligence is all about. In this article we will talk about Business Intelligence tools, benefits & use cases. . What is Business Intelligence.

Business Intelligence 117

Business Intelligence Tools Artificial Inteligence Technical Review 117

Infinidat

MARCH 10, 2021

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Separated Big Data cluster from other programs for Data Science / Discovery to isolate workloads.

Data 80

Data Analytics Cloud Technical Review 80

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective. Check out this list below to see some of them in action: Comcast.

Enterprise 47

Enterprise Cloud Data Healthcare 47

InfoWorld

FEBRUARY 9, 2024

It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment. In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex.

Big Data 92

Big Data Azure Google Cloud Data 92

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 Machine Learning 52

Kentik

MAY 23, 2017

Given the advanced capabilities provided by cloud and big data technology, there’s no longer any justification for legacy monitoring appliances that summarize away all the details and force operators to swivel between siloed tools. ISPs can gain similar advantages by becoming far more data driven.

Network 40

Network Open Source Big Data Load Balancer 40

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 Storage 59

Datavail

MARCH 24, 2020

Loosely defined, a data strategy is a list of high-level objectives and priorities for your enterprise data assets. This includes your plans for handling data at every stage of the pipeline, from collection and storage to integration, analysis, and collaboration.

Strategy 40

Strategy Data Policies Storage 40

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

OCTOBER 29, 2020

Here, we introduce you to ETL testing – checking that the data safely traveled from its source to its destination and guaranteeing its high quality before it enters your Business Intelligence reports. And there’s a big risk that it might happen. What is ETL testing and why do we need it? iCEDQ features demo.

Testing 63

Testing Tools Software Review Technical Review 63

TIBCO - Connected Intelligence

JULY 13, 2020

While COVID-19 presents a short-term hindrance, I recently simulated this experience with my friend Philip Moston, a business intelligence (BI) Architect and Solutions Consultant at TIBCO partner QuinScape, based in Dortmund, home to the highest concentration of breweries in Germany. . Today, we have over 170 employees.

Analytics 58

Analytics Data Virtualization Business Intelligence 58

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Metadata storage. Types of metadata.

Tools 59

Tools Technical Review Software Review Systems Review 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. Pulling it all together.

Artificial Inteligence 298

Artificial Inteligence Data Artificial Intelligence Analytics 298

Kentik

MARCH 27, 2017

I recently had an interesting conversation with an industry analyst about how Kentik customers use our big data network visibility solution for more accurate DDoS detection, automated hybrid mitigation, and deep ad-hoc analytics. I was focused on our current customer base in digital business as well as cloud and service providers.

Enterprise 40

Enterprise Policies Analytics Architecture 40