CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). This applies to his IT group as well, specifically, in using AI to automate the review of customer contracts, Nardecchia says.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. What is DataOps: brief introduction. DataOps vs DevOps.

Analytics 75

Analytics DevOps Development Software Review 75

TechCrunch

JANUARY 10, 2023

In a large-scale survey of IT decision makers published last September, 75% of the respondents said they expected to increase their observability spend in 2022 “significantly” to better plan, deploy and run software. “Every day, executives are making decisions based on data that is incorrect. .”

Data 241

Data Software Review Technical Review Systems Review 241

Altexsoft

APRIL 22, 2020

But, understanding and interpreting data is just a final stage in a long way, as the information goes from its raw format to the fancy analytical boards. So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

Altexsoft

FEBRUARY 8, 2021

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. Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 66

Open Source Analytics Software Review Metrics 66

Altexsoft

NOVEMBER 9, 2021

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. However, more advanced software is capable of analyzing all the available information, discovering inefficiencies, and highlighting areas for improvement.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

TechCrunch

MAY 18, 2022

. “At the time, we all worked at different companies and in different industries yet shared the same struggle with model accuracy due to poor-quality training data. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

FEBRUARY 22, 2022

And breakdowns are just too expensive, especially at a fleet-wide scale (not to mention risking drivers’ lives, losses due to unfulfilled contracts and related downtime, and customer dissatisfaction). Data is gathered from connected sensors and analyzed so that predictions of possible failures can be generated.

Software Review 52

Software Review Technical Review Software Technology 52

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems. So look for their evaluation in Gartner's 2019 reports.

Systems Review 72

Systems Review Storage System Software Review 72

CIO

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

ChatGPT 130

ChatGPT Government Artificial Inteligence Business Intelligence 130

Cloudera

FEBRUARY 8, 2021

Data Enrichment – data pipeline processing, aggregation and management to ready the data for further analysis. Reporting – delivering business insight (sales analysis and forecasting, budgeting as examples). Curated, quality datasets are the backbone of any advanced analytics initiative.

Data 118

Data Technical Review Data Engineering Analysis 118

Cloudera

MAY 3, 2021

In 2020, a McKinsey study reported that “Industry 4.0 data is generated – at the Edge. In the last five years, there has been a meaningful investment in both Edge hardware compute power and software analytical capabilities. Benefits of Streaming Data for Business Owners. Democratization of Data.

Scalability 103

Scalability Agile Data Systems Review 103

Cloudera

JANUARY 27, 2021

The SOC 2 certification helps ensure that applications and code are developed, reviewed, tested, and released following the AICPA Trust Services Principles. To achieve our SOC 2 certification, we proved to our auditors that CDP Public Cloud has suitable policies and controls in place, such as: A secure software development lifecycle.

Cloud 104

Cloud Disaster Recovery Software Review Technical Review 104

Cloudera

MAY 13, 2021

Fixed Reports / Data Engineering jobs . Often mission-critical to the various lines of business (risk analytics, platform support, or data engineering), which hydrate critical data pipelines for downstream consumption. BI Interactive Reports or Dashboards. Ad-Hoc Reports or Exploration.

Data Engineering 73

Data Engineering Cloud Weak Development Team Resources 73

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 126

Weak Development Team Data Technical Review Survey 126

Altexsoft

JANUARY 14, 2021

Though there are countless options for storing, analyzing, and indexing data, data warehouses have remained to the point. When reviewing BI tools , we described several data warehouse tools. In this article, we’ll take a closer look at the top cloud warehouse software, including Snowflake, BigQuery, and Redshift.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

APRIL 13, 2023

Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions. Obviously, it’s all about collecting data from various sources, both external and internal which is possible with specialized technologies.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Hu's Place - HitachiVantara

APRIL 11, 2019

According to the Harvard Business Review , " Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or used at all. That was in a report back in 2017.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

TechCrunch

MAY 7, 2021

This is a result of fintechs being relatively new to the IPO scene compared to their consumer internet or enterprise software counterparts. Analytics as a service: Why more enterprises should consider outsourcing. The analytics-as-a-service (AaaS) market is expected to grow to $101.29 billion by 2026.

Fintech 246

Fintech Windows Healthcare Analytics 246

Altexsoft

SEPTEMBER 10, 2021

The pace of data being created is mind-blowing. For example, Amazon receives more than 66,000 orders per hour with each order containing valuable pieces of information for analytics. Yet, dealing with continuously growing volumes of data isn’t the only challenge businesses encounter on the way to better, faster decision-making.

Tools 52

Tools Data Software Review Technical Review 52

Altexsoft

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Cloudera

NOVEMBER 19, 2020

government loses nearly 150 billion dollars due to potential fraud each year, McKinsey & Company reports. In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Some experts estimate the U.S.

Government 119

Government Artificial Inteligence Machine Learning Data 119

Cloudera

APRIL 9, 2021

In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. A recent Harvard Business Review study confirmed that data is increasingly being spread across data centres, private clouds and public clouds. Multiplatform.

Data 58

Data Software Review Technical Review Architecture 58

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. The ELT workflow.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

UruIT

APRIL 27, 2020

According to the Harvard Business Review , over the next five to 10 years, “business gains will likely stem from getting the right information to the right people at the right time”. Before we break them down, let’s review what a strong development platform might look and feel like, what it should include and provide.

Artificial Inteligence 78

Artificial Inteligence Machine Learning Azure Software Review 78

O'Reilly Media - Ideas

MARCH 1, 2023

This year’s report on the O’Reilly learning platform takes a detailed look at how our customers used the platform. In 2021, we saw that GPT-3 could write stories and even help people write software ; in 2022, ChatGPT showed that you can have conversations with an AI. Now developers are using AI to write software.

Trends 134

Trends Technical Review Technology Software Review 134

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 management tools and key software providers.

Tools 59

Tools Technical Review Software Review Systems Review 59

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer? Data modeling.

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

NOVEMBER 5, 2021

Data analysis, transformation, and decision support revolve around deriving knowledge and insights critical for enhancing patient care. Information dissemination and liaison are about effective sharing of health records, reports, and research findings. Medical codes. Main coding systems in healthcare.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

UruIT

JULY 23, 2019

If so, you’re about to join thousands of software development and data science teams that are applying Machine Learning in their projects and taking advantages of the benefits that this AI discipline offers for creating smart apps. . Or, at least, planning to? Go from idea to deployment in a matter of clicks. Watson Machine Learning.

Artificial Inteligence 81

Artificial Inteligence Machine Learning Azure Software Review 81

Altexsoft

MARCH 14, 2023

A Modern Data Stack (MDS) is a collection of tools and technologies used to gather, store, process, and analyze data in a scalable, efficient, and cost-effective way. Software engineers use a technology stack — a combination of programming languages, frameworks, libraries, etc. — Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59