TechCrunch

JANUARY 26, 2022

It plans to use the money to continue investing in its technology stack, to step up with more business development, and to hire more talent for its team, to meet what it believes are changing tides in the world of data warehousing. Another sign of its growth is a big hire that the company is making.

Analytics 218

Analytics Data Big Data Business Intelligence 218

CIO

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems.

Analytics 320

Analytics Data Analysis Business Analytics 320

TechCrunch

DECEMBER 9, 2020

However, it isn’t just about talent; Google is said to have been very interested in the company’s product, too — in fact, “Dataform web” is now being offered for free going forward. Mining data for insights and business intelligence typically requires a team of data engineers and analysts.

Google Cloud 242

Google Cloud Data Operating System Business Intelligence 242

CIO

FEBRUARY 13, 2023

The economy may be looking uncertain, but technology continues to drive the business and CIOs are investing big in 2023. At the same time, they are defunding technologies that no longer contribute to business strategy or growth.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

CIO

JANUARY 10, 2023

Hiring tech talent in 2023 means navigating an uncertain economy, the effects of widespread tech industry layoffs, and candidates who want to work for a company with a mission and workplace culture that align with their values, including diversity, equity, and inclusion. IT leaders say the best approach is to focus on adaptability.

Trends 309

Trends Recruiting Culture Quality Assurance 309

O'Reilly Media - Ideas

JANUARY 29, 2019

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. We found companies were planning to use deep learning over the next 12-18 months. On one hand, we wanted to see whether companies were building out key components.

Sustainability 84

Sustainability Company Machine Learning Artificial Inteligence 84

CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. It’s an asset “that responds to dynamic business requirements.” Analytics, Business Intelligence

Analytics 334

Analytics Metrics Government Business Intelligence 334

TechCrunch

MAY 26, 2022

But as data continues to grow in scale and complexity, it’s becoming scattered across apps and platforms — often leading to problems where it concerns data quality. He’s the founder of Manta , a data lineage platform that automatically scans an organization’s data sources to build a map of data flows.

Data 228

Data Weak Development Team Enterprise Analysis 228

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Graph technologies and analytics.

Big Data 84

Big Data Technology Tools Cloud 84

Altexsoft

FEBRUARY 11, 2023

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. 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

TechCrunch

DECEMBER 16, 2020

It stems from us seeing the explosive growth of the data warehouse space, both in terms of technology advancements as well as like accessibility and adoption. […] Our goal is to be seen as the company that makes the warehouse not just for analytics but for these operational use cases.” Image Credits: Hightouch.

Data 251

Data B2C Analytics Big Data 251

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. Developing business intelligence gives them a distinct advantage in any industry. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies.

Big Data 52

Big Data Data Development Business Intelligence 52

TIBCO - Connected Intelligence

DECEMBER 16, 2020

Imagine you’re a data engineer at a Fortune 1000 company. Your company has thousands of databases and 14,000 business intelligence users. You use data virtualization to create data views, configure security, and share data. One: Streaming Data Virtualization. Easy, right?

Virtualization 64

Virtualization Data Data Engineering Quality Assurance 64

Hacker Earth Developers Blog

JUNE 26, 2019

In most cases, organizations look at achieving the following using data science: Solve optimization problems : Simply put, reshaping processes by analyzing data; an example could be a logistics company where the supply chain can be optimized so that delivery drivers can use less fuel and reach customers faster.

Data 200

Data How To Recruiting Machine Learning 200

TechCrunch

MARCH 22, 2021

Berlin-based y42 (formerly known as Datos Intelligence), a data warehouse-centric business intelligence service that promises to give businesses access to an enterprise-level data stack that’s as simple to use as a spreadsheet, today announced that it has raised a $2.9 y42 founder and CEO Hung Dang.

Business Intelligence 244

Business Intelligence Software Review B2B Analytics 244

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Datavail

MARCH 31, 2022

Digital analytics offer enterprises an almost limitless array of values because they are as malleable as each business needs them to be. Further, these analytical capacities continue to evolve as more companies develop proprietary analytics to meet their specific sector demands. The Significance of Strategy.

Business Analytics 52

Business Analytics Analytics Artificial Inteligence Strategy 52

Lacework

NOVEMBER 1, 2023

While these may be true in the general macro sense, for many organizations, their data is more akin to their lifeblood. Their data is precious, absolutely essential for their functioning, and the consequences of data loss or leakage can severely threaten the health of the company.

System Design 52

System Design Systems Review System Data 52

Apiumhub

AUGUST 12, 2021

Code Europe serves as a platform for the exchange of best practices and experiences between enthusiasts and world-class experts of the new technology industry. Usually working on Java/Java EE and Spring technologies, but with focused interests like Rich Internet Applications, Testing, CI/CD and DevOps. Currently working for Hazelcast.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

JUNE 14, 2021

This article will explore the topic and its importance, how some insurers are already implementing it as their business model, how to approach personalization, and the challenges companies may encounter trying to implement it. What is personalized insurance, and why is it important? Use of AI and chatbots to personalize communications.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

APRIL 22, 2020

Processing data systematically requires a dedicated ecosystem called data pipeline : a set of technologies that form a specific environment where data is obtained, stored, processed, and queried. So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms.

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Hacker Earth Developers Blog

JUNE 26, 2019

In most cases, organizations look at achieving the following using data science: Solve optimization problems : Simply put, reshaping processes by analyzing data; an example could be a logistics company where the supply chain can be optimized so that delivery drivers can use less fuel and reach customers faster.

Data 100

Data How To Recruiting Machine Learning 100

Capgemini

NOVEMBER 14, 2022

Let’s face it, the inquiry model – ask for insights, wait weeks for answers – does not support today’s pace of business. Leading companies, however, empower the middle of the organization to speed time to market, push digital acceleration, and maintain a competitive advantage. It needed to teach people to fish in the data lake.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

Strategy Driven

FEBRUARY 4, 2021

All this meant a lot of detective work (and not a lot of sales work) which can be automated with sales intelligence software. Sales software is helpful to collect data and insights for companies by using external or internal data to expand sales and increase sales processes. Datanyze focuses on website technology.

Software 34

Software B2B Analytics Business Intelligence 34

Altexsoft

APRIL 13, 2023

Source: Supply Chain Dive Over the last few years, global supply chains have been so severely disrupted – but also enhanced with cutting-edge technologies. Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Business Problem & Background. Conclusion.

Data 82

Data Analytics Cloud Technical Review 82

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

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

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. Note that the above use cases cover network performance monitoring, planning, and business intelligence.

Network 40

Network Open Source Big Data Load Balancer 40

CIO

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. Enter the data lakehouse. Lakehouses redeem the failures of some data lakes.

Data 348

Data Artificial Inteligence Technical Advisors Technical Review 348

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance.

Tools 59

Tools Technical Review Software Review Systems Review 59

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

OpenCredo

JULY 31, 2018

It is hard to imagine, for example, that even fifteen years ago businesses were still debating the need for having an online presence. Who are the people in the organisation best placed to make use of Data in this way, discovering or generating insights to advise the business? In 2018 this is merely common sense.

Artificial Inteligence 40

Artificial Inteligence Machine Learning Data Artificial Intelligence 40

Altexsoft

FEBRUARY 22, 2022

Fleet owners in trucking , car rental , delivery, and other transportation companies know that poorly maintained vehicles burn more fuel, require frequent oiling, and go kaput every other mile. Technological solutions to fleet maintenance. To support your preventive maintenance strategy, you have two technological options.

Software Review 52

Software Review Technical Review Software Technology 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

CIO

APRIL 4, 2023

AI Potential: Powering Our World and Your Business That’s because AI promises to be one of the most transformational technologies of our time. Despite these AI-powered examples, businesses have only just begun to embrace AI, with an estimated 12% fully using AI technology. 1 But this is changing rapidly.

Architecture 130

Architecture Data Analysis Construction 130

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. What is an analytics engineer?

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59