Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data 87

Data Data Engineering Big Data Architecture 87

CIO

MARCH 24, 2023

Doing so can help companies remain responsive, especially as they grow to a size in which it is no longer efficient for individuals to perform cross-functional tasks. Several of the overall benefits of data management can only be realized after the enterprise has established systematic data governance.

Government 357

Government Data Technical Review Policies 357

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

Openxcell

JANUARY 6, 2023

Instead of making substantial investments in databases, software, and hardware, businesses prefer to access their computing power over the internet or in the cloud. Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. Microsoft Azure.

Architecture 52

Architecture Cloud Storage Google Cloud 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. On data warehouses and data lakes. Iterations of the lakehouse.

Data 96

Data Analytics Open Source Architecture 96

Perficient

FEBRUARY 28, 2023

For some background, this client experienced significant growth through acquisition over the past few years, which left their data sprawled across many systems. This data sprawl required significant manual effort to create operational and financial performance dashboards across operating units.

Healthcare 64

Healthcare Technical Review AWS Analytics 64

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

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

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). This is a positive trend but with modern Cloud architectures sometimes the lines can get blurry between the two. Spark is a unified analytics engine for large-scale data processing.

Cloud 98

Cloud Data Azure Analytics 98

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

CTOvision

JANUARY 19, 2014

The place for enterprises to store all data with enterprise grade data management and protection, with access by any system (from legacy to modern, from proprietary to open source). This is the big data news of 2013, from a technology perspective. Business Intelligence 2.0:

Technical Review 109

Technical Review Technology Business Intelligence Systems Review 109

Gorilla Logic

MAY 19, 2021

Not surprisingly, the skill sets companies need to drive significant enterprise software builds, such as big data and analytics, cybersecurity, and AI/ML, are among the most competitive. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more. Skill shortages can delay project kickoffs and delivery.

Software Review 94

Software Review Technical Review Software Development Team Review 94

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 116

Business Intelligence Tools Artificial Inteligence Technical Review 116

Kentik

MARCH 7, 2018

This series of blog posts will examine many aspects of ensuring application performance in cloud-scale enterprise WANs utilizing a hybrid of public and private networks. Private cloud hyperscale data centers will be needed to support Big Data clusters for processing sensor data in real-time along with a whole host of Industry 4.0

Industry 40

Industry Data Center WAN Big Data 40

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

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

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

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. . Are you looking to be able to scale your data volume to a petabyte or more? Accenture Solution.

Data 85

Data Analytics Cloud Technical Review 85

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

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

TIBCO - Connected Intelligence

SEPTEMBER 20, 2019

One of the main objectives with implementing cutting-edge analytics and data management technology is to provide more timely analysis to improve their understanding, planning, and performance evaluation process. Each one is different, but they all work together to effectively and efficiently manage data.

Analytics 20

Analytics Business Intelligence Big Data Enterprise 20

Kentik

MARCH 20, 2017

As such, the network is literally running the business, carrying the revenue. That also means that the network is more than a utility, it’s a key source for operational and business intelligence, because it’s in a unique position to see both the activity and performance of digital business.

Internet 40

Internet Enterprise Conference Survey 40

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

Altexsoft

JANUARY 22, 2020

Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. A complete guide to business intelligence and analytics. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

APRIL 13, 2023

to see where freight is in real time and what the ETA is, share this information with customers, monitor and analyze fleet/carrier performance, and much more. Previously, control towers were seen as multi-faceted dashboards to monitor performance. to develop all the data architecture and analytics solutions.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

CIO

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. The lakehouse will also help with fraud prevention.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

TechCrunch

DECEMBER 9, 2020

For many organizations, the shift to cloud computing has played out more realistically as a shift to hybrid architectures, where a company’s data is just as likely to reside in one of a number of clouds as it might in an on-premise deployment, in a data warehouse or in a data lake.

Data 253

Data Big Data Analytics Enterprise 253

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

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

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. Data lineage graph. Types of metadata. Source: Oracle.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

APRIL 10, 2024

Higher-level languages, automation, low-code and no-code development platforms, and better programming environments have been gradually reducing the need for IT staff to perform low-level, routine tasks for years so they can take on more innovative challenges. In fact, people normally gain emotional intelligence with age, he says.

Artificial Inteligence 338

Artificial Inteligence Generative AI Training Coaching 338

Altexsoft

APRIL 22, 2020

In its core, data science is all about getting data for analysis to produce meaningful and useful insights. The data can be further applied to provide value for machine learning , data stream analysis , business intelligence , or any other type of analytics. We need to store extracted data somewhere.

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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

Kentik

MAY 31, 2016

In the first post we discussed the need for a Big Data approach to network management in order to support agile business models and rapid innovation. In the second post we looked at how insights from a Big Data approach to network management enable data-driven network operations.

Big Data 40

Big Data Data Analytics Weak Development Team 40

Cloudera

FEBRUARY 8, 2024

Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time.

Groups 94

Groups Technical Review Performance AWS 94

Altexsoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Storage IoT 52