TechCrunch

NOVEMBER 3, 2021

The company lets you install their solution on your cloud of choice such as Amazon, Microsoft or Google and then capture the data as it comes into your system, using Blotout to collect the permissions and comply with each law, while giving the customer full control of the data.

Data 224

Data Compliance Authentication Data Engineering 224

TechCrunch

APRIL 12, 2022

According to a 2021 Wakefield Research report , enterprise data engineers spend nearly half their time building and maintaining data pipelines. “Data science is very academic, which directly affects machine learning.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

AWS Machine Learning - AI

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JANUARY 27, 2021

Achieving SOC 2 is one of the first milestones on our aggressive security and compliance roadmap. You can expect to see further compliance achievements, including expanding Cloudera’s ISO27001 certification to include CDP Public Cloud, FedRAMP, and more, over the coming quarters. Why is SOC 2 Important?

Cloud 103

Cloud Disaster Recovery Software Review Technical Review 103

d2iq

JANUARY 18, 2022

D2iQ is an AWS Containers Competency Partner , and D2iQ Kaptain is an enterprise Kubeflow product that enables organizations to develop and deploy machine learning workloads at scale. Complexity: There are lots of cloud-native and AI/ML tools on the market.

Artificial Inteligence 72

Artificial Inteligence Machine Learning AWS Weak Development Team 72

Datavail

JUNE 20, 2023

Percona Live 2023 was an exciting open-source database event that brought together industry experts, database administrators, data engineers, and IT leadership. 93% of large enterprises use database monitoring and management solutions. 32% of large enterprise database deployments use Database-as-a-Service offerings.

Open Source 52

Open Source Database Administration Survey AWS 52

Xebia

MARCH 10, 2021

For our use case: breaking down the wall of confusion between Data Science and Operations of Data Applications in an enterprise setting, principles 3 and 4 are most important. Therefore we state: Enterprises often create a ‘wall of confusion’ when starting an advanced analytics capability in their organisation.

DevOps 130

DevOps Data Analytics Policies 130

OTS Solutions

MARCH 14, 2019

In just the last few years, a large number of enterprises have started to work on incorporating an artificial intelligence strategy into their business. New teams and job descriptions relating to AI will need to be created by adding data scientists, data engineers and machine learning engineers to your staff.

Artificial Inteligence 140

Artificial Inteligence Artificial Intelligence Strategy Technical Review 140

TIBCO - Connected Intelligence

JANUARY 11, 2021

Enterprise-scale MDM adoption is a multi-year journey, not a one time event. Over time you can expand your MDM use to more domains and eventually reach enterprise scale. Underestimating data engineering workloads . Every MDM project requires that you understand, access, and integrate your source data in some way.

Technical Advisors 54

Technical Advisors Data Data Engineering Compliance 54

Mentormate

JANUARY 11, 2022

With hundreds of active clients and projects each year, MentorMate is in an excellent position to share our perspective on what’s happening across different industries, technology stacks, and business environments from startup to enterprise. In some cases, this even includes de-identifying the information due to compliance concerns.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

Cloudera

APRIL 9, 2021

You may recall from the previous blogs in this series that ECC is leveraging the Cloudera Data Platform (CDP) to cover all the stages of its data life cycle. Data Collection – streaming data. Data Enrichment – data engineering. Reporting – data warehousing & dashboarding.

Machine Learning 98

Machine Learning Artificial Inteligence Data Data Engineering 98

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Private clouds are not simply existing data centers running virtualized, legacy workloads. They require highly modernized digital application and service environments running on true cloud platforms like Hitachi Enterprise Cloud.

Cloud 78

Cloud Google Cloud Azure AWS 78

O'Reilly Media - Data

SEPTEMBER 24, 2018

Data science is the sexy thing companies want. The data engineering and operations teams don't get much love. The organizations don’t realize that data science stands on the shoulders of DataOps and data engineering giants. Let's call these operational teams that focus on big data: DataOps teams.

Enterprise 198

Enterprise Data Big Data Disaster Recovery 198

Cloudera

JANUARY 19, 2018

Last January we launched Apache Kudu, as part of Cloudera Enterprise 5.10. This blog highlights three use cases where real-time makes a real difference: time series data, machine data analytics, and online reporting. Cloudera Data Science Workbench: Self-Service Data Science for the Enterprise.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. A data catalog enables self-service BI, seamless data collaboration, integrated communication, and the sharing of internal expertise, all built on a foundation of trust.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

TIBCO - Connected Intelligence

OCTOBER 15, 2020

Towards these trends, our clients have significantly invested in data-related technologies and talent over the past several years, including: Data governance to cater to enterprise-level financial reporting and regulatory compliance as an example. Self-service data discovery (e.g., Self-service data discovery (e.g.,

Virtualization 50

Virtualization Data Energy Innovation 50

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use. People selling information.

Government 73

Government Artificial Inteligence Enterprise Strategy 73

Altexsoft

SEPTEMBER 9, 2022

Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance. To ensure metadata quality as well as correct application of metadata policies and proper compliance to requirements and standards, audits have to be regularly conducted by data stewards. It provides data consumers with.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

TIBCO - Connected Intelligence

JUNE 16, 2021

To better understand how UltimSoft help organizations transition to next-generation customer data platforms, I spoke with UltimoSoft CEO and founder, Dr. Subhash Pasumarthy. UltimoSoft is an enterprise application services provider that helps organizations efficiently design and deploy IT solutions. What are they trying to achieve?

Data 29

Data Weak Development Team Virtualization Compliance 29

O'Reilly Media - Ideas

FEBRUARY 11, 2019

The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco , where leading companies and speakers will share their learnings on the topics covered in this post. AI and machine learning in the enterprise. AI and machine learning in the enterprise. Data Platforms. Deep Learning.

Big Data 87

Big Data Technology Tools Cloud 87

Cloudera

FEBRUARY 19, 2018

With a modern, top-notch, in-memory columnar database it offers full coverage of all major industries and business processes, from data entry to finance, legal, compliance, production planning, and HR. It’s the de facto choice for all major corporations on the planet to manage their business data. Governance. Cataloging.

Data 46

Data Government Big Data Compliance 46

Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning. Modern data warehousing.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Cloudera

AUGUST 31, 2021

It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes. Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. Business Problem & Background.

Data 82

Data Analytics Cloud Technical Review 82

O'Reilly Media - Ideas

NOVEMBER 13, 2018

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

TIBCO - Connected Intelligence

SEPTEMBER 15, 2020

With everyone on the same page, it is much easier to align business and data management related processes and definitions and thus reduce the reconciliation and remediation costs. Better regulatory compliance and avoidance of fines, fees, and penalties by enabling better adherence to compliance and corporate governance frameworks.

How To 26

How To Compliance Government Insurance 26

DataRobot

MARCH 10, 2022

DataRobot and Snowflake Jointly Unleash Human and Machine Intelligence Across the Industrial Enterprise Landscape. Python is unarguably the most broadly used programming language throughout the data science community. The “Fourth Industrial Revolution” was coined by Klaus Schwab of the World Economic Forum in 2016.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Cloudera

DECEMBER 10, 2020

CDW includes two highly scalable and performant Apache open-source engines – Impala and Hive LLAP – that have proven themselves in hundreds of enterprises for business-critical data warehousing. Today, enterprises want data warehouses that support on-demand consumption.

Data 98

Data Technical Review Storage Systems Review 98

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?

System Design 52

System Design Systems Review System Data 52

TechCrunch

JUNE 22, 2022

He built his own SQL-based tool to help understand exactly what resources he was using, based on data engineering best practices. Pats believes that cloud infrastructure is locked in the past from a data standpoint, and he wanted to push it into the modern age with CloudQuery.

Infrastructure 206

Infrastructure Cloud Open Source Data Engineering 206

Cloudera

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. This leads to wasted time and effort during research and collaboration or, worse, compliance risk.

Data 41

Data Load Balancer Machine Learning Artificial Inteligence 41

Altexsoft

JUNE 11, 2021

Now, scale it to the enterprise level and just imagine how many processes comprise the daily workflow — and how many optimization opportunities there are IF you could break down and analyze every step of every process. Another challenge concerns the lack of integration for cross-organizational process mining.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Existek

JANUARY 11, 2022

They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. Security, identity, and compliance. Both small businesses and enterprises shift computing tasks to the cloud. Choosing cloud-based solutions is also about getting great data, account, and workload protection. Data Engineer $130 000.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

O'Reilly Media - Ideas

MARCH 18, 2020

The update sheds light on what AI adoption looks like in the enterprise— hint: deployments are shifting from prototype to production—the popularity of specific techniques and tools, the challenges experienced by adopters, and so on. One-sixth of respondents identify as data scientists, but executives—i.e., Model degradation is the No.

Enterprise 134

Enterprise Survey Technical Review Weak Development Team 134