TechCrunch

FEBRUARY 24, 2021

, and millions and perhaps billions of calls flung at the database server, data science teams can no longer just ask for all the data and start working with it immediately. Big data has led to the rise of data warehouses and data lakes (and apparently data lake houses ), infrastructure to make accessing data more robust and easy.

Data 271

Data Business Intelligence Big Data Data Engineering 271

TechCrunch

NOVEMBER 10, 2020

Explo , a member of the Y Combinator Winter 2020 class, which is helping customers build customer-facing business intelligence dashboards, announced a $2.3 million seed round today. Investors included Amplo VC, Soma Capital and Y Combinator along with several individual investors.

CTO Coach 196

CTO Coach Business Intelligence Travel Data Engineering 196

O'Reilly Media - Data

APRIL 3, 2018

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 154

Machine Learning Artificial Inteligence Company Case Study 154

TechCrunch

FEBRUARY 2, 2022

. “But if you look at state of the art companies like Amazon, then it is not the marketing teams that are putting together this customer data infrastructure — it is very much the engineering teams, the data teams, maybe the growth team — but the data team inside of that growth team — they are building this infrastructure.

Data 204

Data Machine Learning Artificial Inteligence Architecture 204

CTOvision

AUGUST 1, 2015

Editor's note: The highly respected venture capital firms Blu Venture, Sequoia, and Conversion Capital have announced their support and funding of Immuta, a next-gen enterprise data management startup. We are thrilled to be supporting such a disruptive business for enterprise cloud usage,” said T. Richard Stroupe, Jr.

Big Data 114

Big Data System Data Software Engineering 114

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. The reasons for the dismal statistics are many: Often the data itself is siloed across many databases that aren’t set up for or accessible by analytics programming. Contact us today.

Business Analytics 52

Business Analytics Analytics Artificial Inteligence Strategy 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. AI and machine learning in the enterprise. AI and machine learning in the enterprise. Temporal data and time-series analytics. Deep Learning.

Big Data 86

Big Data Technology Tools Cloud 86

Lacework

NOVEMBER 1, 2023

When architecting data systems, a key philosophy is keeping customer privacy front and center both in the design choices made and and options presented to the user, while ensuring the ability to meet business needs and service criteria. What is privacy? A mart is a group of aggregated tables (e.g.,

System Design 52

System Design Systems Review System Data 52

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.

Data 82

Data Analytics Cloud Technical Review 82

Altexsoft

APRIL 13, 2023

To store all this diverse information, you’ll have to utilize a centralized data repository such as a data warehouse or data lake. You can also consider a cloud data lakehouse as an option since it addresses the limitations of the aforementioned repository types and works with various data workloads.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. Watch this video to get an overview of CDW. .

Data 98

Data Technical Review Storage Systems Review 98

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

CIO

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Architecture 130

Architecture Data Analysis Construction 130

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

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

Altexsoft

MARCH 31, 2020

Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data? You need to have infrastructure, hardware and/or software, that will allow you to do that. You need an efficient data pipeline. What is a data pipeline?

Data 76

Data Storage Analytics Data Center 76

TechCrunch

JUNE 17, 2021

Now, three alums that worked with data in the world of Big Tech have founded a startup that aims to build a “metrics store” so that the rest of the enterprise world — much of which lacks the resources to build tools like this from scratch — can easily use metrics to figure things out like this, too.

Metrics 247

Metrics Tools Data Big Data 247

Altexsoft

OCTOBER 24, 2019

While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

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. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Cloudera

FEBRUARY 8, 2021

Security & Governance – an integrated set of security, management and governance technologies across the entire data lifecycle. 1 The enterprise data lifecycle. Data Enrichment Challenge. Building a Pipeline Using Cloudera Data Engineering. 2 ECC data enrichment pipeline. Conclusion.

Data 114

Data Technical Review Data Engineering Analysis 114

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. Business Intelligence Analyst.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Datavail

JUNE 15, 2023

“It unifies the business model across all the different types of analytics workloads, whether they’re SQL, machine learning – whatever job you want, you can use the same compute infrastructure. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

Azure 52

Azure Analytics Storage Generative AI 52

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Cloudera

NOVEMBER 19, 2020

The Association of Certified Fraud Examiners reports the use of artificial intelligence and machine learning in anti-fraud programs is expected to almost triple in the next two years. Inordinate time and effort are devoted to cleaning and preparing data, resulting in data bottlenecks that impede effective use of anomaly detection tools.

Government 114

Government Artificial Inteligence Machine Learning Data 114

Altexsoft

JULY 19, 2022

It’s easiest to understand the concept of a data mesh by looking at the core principles behind it which we’re going to uncover more extensively later on. They are: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a service, and. But not only.

Architecture 52

Architecture Data Analytics Data Engineering 52

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

TechCrunch

APRIL 13, 2021

The promise of Meroxa is that can use a single platform for their various data needs and won’t need a team of experts to build their infrastructure and then manage it. Existing investors Root, Amplify and Hustle Fund also participated in this round, which together with the company’s previously undisclosed $4.2

Data 248

Data Software Engineering Open Source Engineering 248

Altexsoft

AUGUST 21, 2019

Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data. Using specific tools and practices, businesses implement these methods to generate valuable insights. Data engineer. Data Pipeline Development.

Development 44

Development Software Engineering Data Engineering Architecture 44

Altexsoft

OCTOBER 2, 2020

Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Fitting into wider enterprise architecture, it outlines how data is collected, integrated, transformed, stored, and used. Data analytics and business intelligence: drawing insights from data.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g.,

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

SEPTEMBER 9, 2018

Cloudera Altus offers several key integrated services for data warehousing needs: Altus Data Engineering for building data pipelines and running ETL workflows. Altus Data Warehouse for SQL and business intelligence reporting and analytics. SDX for Altus for shared data context (data catalog).

Data 40

Data Data Engineering Analytics Cloud 40

Altexsoft

OCTOBER 8, 2021

This often includes such procedures as data profiling (searching for errors and inconsistencies), cleansing (removing duplicates, corrupted items, etc.), Data integration process. On the enterprise level, data integration may cover a wider array of data management tasks including. Data loading. Ease of use.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Altexsoft

OCTOBER 3, 2019

The platform provides “ business intelligence, planning, and predictive capabilities within one product” and uses AI and ML. Data engineer builds interfaces and infrastructure to enable access to data. So, data engineers make data pipelines work. Develop UI of a solution.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Altexsoft

DECEMBER 9, 2020

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Data warehouse architecture.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

MARCH 30, 2023

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64