CIO

JUNE 7, 2022

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. In business, predictive analytics uses machine learning, business rules, and algorithms.

Analytics 338

Analytics Data Analysis Business Analytics 338

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

Exadel

FEBRUARY 20, 2023

The technological landscape has evolved to include AI assistants, self-driving cars, and machine learning solutions that process data in a blink of an eye. Major Players for AI in the Cloud For the scope of this article, AI is defined as machine learning, since ML is the biggest constituent of the technology.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

DECEMBER 20, 2022

In that sense, access to the auction is more conservative and can lead to inefficiencies in the use of assets, as some of the energy produced may be discarded if it is not saleable in the intraday market. McKinsey estimates that the use of data-driven technologies can drive operating and maintenance cost savings of more than 12%.

Energy 81

Energy Analytics Data Machine Learning 81

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. Building an AI or machine learning model is not a one-time effort.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

SEPTEMBER 29, 2020

A TPC-DS 10TB dataset was generated in ACID ORC format and stored on the ADLS Gen 2 cloud storage. Cloudera Data Warehouse vs HDInsight. Finally, CDW is offered in CDP along with other data lifecycle services – Data Engineering, Operational Database, Machine Learning, and Data Hub.

Azure 118

Azure Data Comparison Virtualization 118

Cloudera

JANUARY 20, 2021

Digital transformation is a hot topic for all markets and industries as it’s delivering value with explosive growth rates. Reporting – delivering business enterprise insight (sales analysis and forecasting, market research, budgeting as examples). STEP 3: Monitor data throughput from each factory.

Data 107

Data Artificial Inteligence Analytics Machine Learning 107

O'Reilly Media - Ideas

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). You’re responsible for the design, the product-market fit, and ultimately for getting the product out the door. Machine learning adds uncertainty.

Product Management 139

Product Management Artificial Inteligence Machine Learning Software Review 139

Altexsoft

JUNE 14, 2021

This is possible because their machine learning model is retrained almost daily. On top of that, the company uses big data analytics to quantify losses and predict risks by placing the client into a risk group and quoting a relevant premium. Or your data quality may be low to reach project feasibility.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

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

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If so, you know about the failed economics of some cloud-native solutions on the market today. If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse.

Data 98

Data Technical Review Storage Systems Review 98

Existek

JANUARY 11, 2022

It’ll be interesting to discover how market-leading providers set new standards and alter approaches to cloud computing. Azure vs AWS market share. AZURE VS AWS MARKET SHARE. It might be challenging as it requires a detailed analysis of the business-specific needs and a deeper understanding of the overall market situation. .

Azure 52

Azure AWS Cloud How To 52

Altexsoft

AUGUST 25, 2020

Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. 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.

Big Data 75

Big Data Data Engineering Engineering Data 75

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. I agree; learn as much as you can.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Altexsoft

JANUARY 27, 2022

As of today, different machine learning (and specifically deep learning) techniques capable of processing huge amounts of both historic and real-time data are used to forecast traffic flow, density, and speed. Extraction of social media data for traffic prediction. Machine learning approach.

Machine Learning 69

Machine Learning Artificial Inteligence Transportation Network 69

Altexsoft

SEPTEMBER 9, 2022

These are important for SEO purposes because search engines use them to “understand” what the page is about and how it has to be displayed and ranked in search results. Besides, they have to attract users to visit the website, so it’s a powerful marketing tool. It aims at making data assets understandable and discoverable for users.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

AUGUST 19, 2022

So, in this article, we’ll talk about the current BI market leader – Microsoft Power BI – and discuss its functionality, pros and cons, and alternatives. Microsoft Power BI is an interactive data visualization software suite developed by Microsoft that helps businesses aggregate, organize, and analyze data. What is Power BI?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action. To buy or build?

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JUNE 6, 2019

Forecasting demand with machine learning in Walmart. Systems that rely on machine learning are capable of analyzing a multitude of data points, finding subtle patterns (indicating changes in customer preferences, behavior, or satisfaction) which can be non-obvious for a human. data is analyzed. “We

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.

Data Engineering 103

Data Engineering Engineering Data Tools 103

Altexsoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. 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. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

APRIL 26, 2023

At its core, CDP Private Cloud Data Services (“the platform”) is an end-to-end cloud native platform that provides a private open data lakehouse. It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment.

Cloud 63

Cloud Data Load Balancer Storage 63

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Erik Bernhardsson

DECEMBER 6, 2022

Lets let the right workflows emerge from what makes teams the most productive, and lets let data workflows stand on their own feet. Let's make data teams more productive! I started looking at this a few years ago, looked at the absurdly crowded market landscape , and spent a lot of time talking to very smart people.

CTO Coach 242

CTO Coach Fractional CTO Software Engineering Serverless 242

Altexsoft

APRIL 26, 2022

The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. The former extracts and transforms information before loading it into centralized storage while the latter allows for loading data prior to transformation. Each node has its own disk storage. Database storage layer.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

JANUARY 25, 2024

That’s noise; we won’t insult your intelligence by claiming that “flat in a down market” is really a gain. It’s certainly fair to ask whether a language as popular as Python has gathered all the market share that it will get. There are always new languages ready to take some of Python’s market share. SQL Server also showed a 5.3%

Trends 118

Trends Technical Review Technology Artificial Inteligence 118

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so? Scalability opportunities.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. 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. Source: Allied Market Research. What is Hadoop?

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

NOVEMBER 9, 2021

When you go to the local farmer’s market to buy fresh produce from a seller you have known for years or try on a trendy outfit after having an ice cream in your favorite mall, well, it’s a simple way to enjoy life. Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

MARCH 18, 2021

This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type. Cloud data warehouses such as Snowflake, Redshift, and BigQuery also support ELT, as they separate storage and compute resources and are highly scalable.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

StubHub

AUGUST 8, 2019

They work across many departments at StubHub, including finance, marketing, and communications. Rudra Gandhi, Data Engineering intern, (San Jose State University, Mathematics and Computer Science Major): As a company, I thought that StubHub is an interactive platform for its audiences and accepts feedback very nicely.

Technical Review 8

Technical Review Software Review Software Engineering Sport 8

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

AUGUST 21, 2019

Data obsession is all the rage today, as all businesses struggle to get data. But, unlike oil, data itself costs nothing, unless you can make sense of it. Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data.

Development 44

Development Software Engineering Data Engineering Architecture 44