TechCrunch

AUGUST 4, 2022

Company co-founder and CEO Michael Driscoll says he started the company in 2020 with the premise that the business intelligence was broken. He and his team of engineers, most of whom had came from his team at Snap, went to work on building a better solution for a broader audience. “I

Open Source 246

Open Source Metrics Enterprise Business Intelligence 246

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. The opportunity that Firebolt is targeting is a ripe one in the world of enterprise.

Analytics 218

Analytics Data Big Data Business Intelligence 218

TechCrunch

MAY 26, 2022

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-driven decisions can only be as good as the quality of the underlying data sets and analysis. ” Kratky said.

Data 228

Data Weak Development Team Enterprise Analysis 228

CIO

DECEMBER 14, 2023

Salesforce is updating its Data Cloud with vector database and Einstein Copilot Search capabilities in an effort to help enterprises use unstructured data for analysis. The Einstein Trust Layer is based on a large language model (LLM) built into the platform to ensure data security and privacy.

Artificial Inteligence 174

Artificial Inteligence Analysis Data Cloud 174

TechCrunch

NOVEMBER 2, 2022

When Berlin-based Y42 launched in 2020 , its focus was mostly on orchestrating data pipelines for business intelligence. “The use case for data has moved beyond ad hoc reporting to become the very lifeblood of a company. No-code business intelligence service y42 raises $2.9M seed round.

Data 203

Data Business Intelligence Open Source Government 203

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

TechCrunch

FEBRUARY 24, 2021

From there, it offers a full-text search that allows users to quickly find data as well as “heat map” signals in its search results which can quickly pinpoint which columns of a dataset are most used by applications within a company and have the most queries that reference them. Photo via Select Star. Photo via Select Star.

Data 271

Data Business Intelligence Big Data Data Engineering 271

CIO

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

Analytics 203

Analytics Data Analysis Business Analytics 203

TechCrunch

SEPTEMBER 1, 2022

. “Our thesis was that while companies collect mountains of data, the return on investment on it remains low because it’s predominantly used in dashboards and reporting, not daily actions and automation,” Akmal told TechCrunch in an email interview. These people are in high demand and there aren’t enough to go around.

Weak Development Team 223

Weak Development Team Marketing Analytics Business Intelligence 223

CIO

AUGUST 18, 2022

Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data.

Data 210

Data Technical Review Technical Advisors Artificial Inteligence 210

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

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

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. Understand the importance of timeliness and quality of the data on which important decisions are being made.

Analytics 205

Analytics Metrics Government Business Intelligence 205

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.

Artificial Inteligence 157

Artificial Inteligence Machine Learning Company Case Study 157

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

CIO

FEBRUARY 13, 2023

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 218

Budget Artificial Inteligence Technical Review VR 218

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

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 122

Data Technical Review Data Engineering Analysis 122

TechCrunch

DECEMBER 16, 2020

. “We have a class of things here that connect to a data warehouse and make use of that data for operational purposes. There’s no industry term for that yet, but we really believe that that’s the future of where data engineering is going.

Data 251

Data Analytics B2C Big Data 251

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Read why the future of data lakehouses is open.

Data 94

Data Analytics Artificial Inteligence Machine Learning 94

TechCrunch

APRIL 13, 2021

” It’s worth noting that Meroxa uses a lot of open-source tools but the company has also committed to open-sourcing everything in its data plane as well. “This has multiple wins for us, but one of the biggest incentives is in terms of the customer, we’re really committed to having our agenda aligned.

Data 248

Data Software Engineering Open Source Engineering 248

TechCrunch

FEBRUARY 2, 2022

“What makes RudderStack unique is its end-to-end data pipelines for customer data optimized for data warehouses,” said Praveen Akkiraju, Managing Director at Insight Partners, who will join the company’s board.

Data 204

Data Artificial Inteligence Machine Learning Architecture 204

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 scientists.

Development 44

Development Software Engineering Data Engineering Architecture 44

Kentik

MAY 2, 2016

In part 1 of this series we introduced Kentik Data Engine™, the backend to Kentik Detect™, which is a large-scale distributed datastore that is optimized for querying IP flow records (NetFlow v5/9, sFlow, IPFIX) and related network data (GeoIP, BGP, SNMP). Want to try KDE with your own network data? Time: 0.458s.

Data Engineering 40

Data Engineering Engineering .Net Data 40

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

NOVEMBER 19, 2020

It enables public sector agencies to tap the power of big data and machine learning by managing volume, velocity, and variety of data, bringing unified governance, data integration, and open-source data management capabilities across all cloud and hybrid-cloud environments. Fraudulent Activity Detection.

Government 122

Government Artificial Inteligence Data Machine Learning 122

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

Architecture 84

Architecture Data Artificial Inteligence Artificial Intelligence 84

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. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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. All this data is in motion.

Virtualization 64

Virtualization Data Data Engineering Quality Assurance 64

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 125

Weak Development Team Data Technical Review Survey 125

AWS Machine Learning - AI

AUGUST 8, 2024

RAG optimizes language model outputs by extending the models’ capabilities to specific domains or an organization’s internal data for tailored responses. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

Artificial Inteligence 117

Artificial Inteligence Data Generative AI AWS 117

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

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses.

Data 98

Data Analytics Open Source Architecture 98

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. Deep Learning.

Big Data 85

Big Data Technology Tools Cloud 85

Altexsoft

MARCH 18, 2021

The primary difference resides in WHERE and WHEN data transformation and loading happens. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. ELT comes to the rescue.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way. Kudu has this covered.

Analytics 95

Analytics Artificial Inteligence Machine Learning Telecommunications 95

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 78

Architecture Data Analysis Enterprise 78