SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING: MICROSOFT SQL SERVER EVALUATION: AZURE VIRTUAL MACHINES VS. AMAZON WEB SERVICES EC2
GigaOm
March 01, 2021
This report outlines the results from a GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances
Microsoft SQL Server Microsoft on Azure Virtual Machines (VM)
Both are installations of Microsoft SQL Server, and we tested Red Hat Enterprise Linux OS.
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Tags: Analytics, Big Data, Cloud
Modernize Data Warehousing: Beyond Performance, The Importance of Other Key Attributes
Vertica
February 02, 2021
Organizations looking for enterprise data warehouses (EDWs) cannot afford to base their evaluation on query price-performance alone. There’s much more to it. You also need capabilities that reduce the time needed for configuration, management, tuning, and other tasks that can take away from valuable time spent on business analytics.
This new whitepaper from McKnight Consulting Group explores factors that can reduce the costs of analytics far beyond performance, such as licensing structure, data storage, support for non-structured data, concurrency scaling, and much more. Download your copy today, and make a well-informed decision when choosing an EDW platform.
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Tags: Big Data, Cloud, Data Center
BENCHMARK REPORT: CONTAINERIZED SQL SERVER PERFORMANCE TESTING
GigaOm
January 13, 2021
We conducted an unbiased benchmark study of SQL Server 2019 running on the most promising Kubernetes platforms available on the market today. Our goal is to help each customer determine the best-suited platform to run Microsoft SQL Server based on their individual requirements.
Read the full benchmark report, which provides insight to help IT professionals, DevOps engineers, platform architects and information security practitioners evaluate a Kubernetes platform optimal for running I/O intensive Microsoft SQL Server applications.
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Tags: Big Data, Cloud, Data Center, DevOps
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
MCG
January 11, 2021
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a field test derived from the industry standard TPC Benchmark DS (TPC-DS) comparing five relational analytical databases based on scale-out cloud data warehouses.
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Tags: Big Data, Cloud
SQL TRANSACTION PROCESSING PRICE-PERFORMANCE TESTING: AZURE VIRTUAL MACHINES VS. AWS EC2 INSTANCES
GigaOm
November 11, 2020
Get free access to this 30-page GigaOm Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings: Microsoft SQL Server on Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instances; Microsoft SQL Server Microsoft on Azure Virtual Machines (VM). Both are installations of Microsoft SQL Server and we tested on both Windows Server OS and Red Hat Enterprise Linux OS.
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Tags: Big Data, Cloud, Data Center
APPLICATION CACHE PERFORMANCE PRODUCT EVALUATION: AZURE CACHE FOR REDIS
GigaOm
September 07, 2020
Applications and their performance requirements have evolved dramatically in today’s landscape. The cloud enables enterprises to differentiate and innovate with APIs and microservices at a rapid pace. Cloud providers, like Azure, allow microservice endpoints to be cloned and scaled in a matter of minutes. The cloud offers elastic scalability compared to on-premises deployments, enabling faster server deployment and application development and less costly compute. In this paper, we reveal the results of application performance testing we completed both with and without Azure Cache for Redis on top of Azure SQL Database and Azure Database for PostgreSQL.
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Tags: Big Data, Cloud, Data Center
MCG ENTERPRISE CONTRIBUTION RANKING REPORT FOR CLOUD DATA MANAGEMENT AND INTEGRATION FOR CLOUD DATA WAREHOUSES AND DATA LAKES
MCG
August 05, 2020
In this paper, we have undertaken an ambitious goal of evaluating the current vendor landscape and assessing which tools and platforms have made, or are in the process of making, the leap to this new generation of data management and integration capabilities.
The vendors/products chosen were:
AWS (Glue)
Azure (Azure Data Factory)
Cloudera (Cloudera Replication Manager)
Fivetran
Google (Alooma)
IBM
Informatica
Matillion
Oracle
SAP
Talend
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Tags: Big Data, Cloud, Data Center
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
August 05, 2020
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a field test derived from the industry standard TPC Benchmark DS (TPC-DS) comparing five relational analytical databases based on scale-out cloud data warehouses.
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Tags: Big Data, Cloud, Data Center
EMPOWERING USERS TO MINE THE DATA LAKE, ENERGIZE A DATA CATALOG AND RETURN BIG ROI
GigaOm
July 14, 2020
In this Business Technology Impact report, we take a look at a large multi-national firm and its implementation of a data lake and data catalog. Within the company, a small team worked to transform the data lake from an underutilized, misunderstood ‘white elephant’ into a resource that drove the company’s growth and innovation.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE APPLICATION SECURITY TESTING, PRODUCT EVALUATION: NGINX APP PROTECT VS. MODSECURITY (PLUS AWS WEB Application)
GigaOm
July 13, 2020
Data, web, and application security has evolved dramatically over the past few years. Just as new threats abound, the architecture of applications—how we build and deploy them—has changed. We’ve traded monolithic applications for microservices running in containers and communicating via application programming interfaces (APIs)—and all of it deployed through automated continuous integration/continuous deployment (CI/CD) pipelines. The frameworks we have established to build and deploy applications are optimized for time to market—yet security remains of utmost importance.
Our focus is specifically on approaches to securing apps, APIs, and microservices that are tuned for high performance and availability. We define “high performance” as companies that experience workloads of more than 1,000 transactions per second (tps) and require a maximum latency below 30 milliseconds across the landscape.
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Tags: Big Data, Cloud, Data Center
API AND MICROSERVICES MANAGEMENT PRODUCT EVALUATION: KONG ENTERPRISE, APIGEE EDGE, AND APIGEE EDGE MICROGATEWAY
GigaOm
July 07, 2020
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations comprise a vast array of applications and systems, many of which have turned to APIs to exchange data as the glue to hold these heterogeneous artifacts together. In this paper, we reveal the results of performance testing we completed across three API and Microservices Management platforms: Kong Enterprise, Apigee Edge, and Apigee Edge Microgateway.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE CLOUD DATA WAREHOUSE VENDOR EVALUATION
GigaOm
June 16, 2020
This authoritative report from GigaOm Research, a respected independent industry analyst firm, details the key performance and cost criteria to guide your cloud data warehouse selection.
“Price and performance are critical points of interest…our analysis reveals Avalanche to be the industry leader on this criterion.”
Highlights from the report:
Key factors to consider when evaluating a hybrid cloud data warehouse
Head-on vendor comparisons across performance and cost using industry standard TPC-H benchmark
Vendors analyzed include Actian Avalanche, Snowflake, Amazon Redshift, Microsoft Azure Synapse and Google BigQuery
Assessment of single user and multiple concurrent users scenarios
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Tags: Big Data, Cloud, Data Center
DATA PIPELINE PLATFORM COMPARISON
GigaOm
June 08, 2020
In this report, we compare the three major data pipeline platforms: Matillion, Stitch, and Fivetran; and run them through a series of selected tests that highlight their degree of automation, ease of setup, and documentation. We evaluated aspects that include the time and effort required to set up a source-destination connection, the degree of automation throughout the process, and the quality of documentation to support the effort. These areas address the three major “humps of work” we have encountered in our field work with data pipelines.
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Tags: Big Data, Cloud, Data Center
DATA PIPELINE PLATFORM COMPARISON
GigaOm
April 20, 2020
In this report, we compare the three major data pipeline platforms: Matillion, Stitch, and Fivetran; and run them through a series of selected tests that highlight their degree of automation, ease of setup, and documentation. We evaluated aspects that include the time and effort required to set up a source-destination connection, the degree of automation throughout the process, and the quality of documentation to support the effort. These areas address the three major “humps of work” we have encountered in our field work with data pipelines.
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Tags: Big Data, Cloud, Data Center
PRICE PERFORMANCE IN MODERN CLOUD DATABASE MANAGEMENT SYSTEMS
Teradata
April 15, 2020
The pace of relational analytical databases deploying in the cloud are at an all-time high. The goal of this paper is to provide information to help a customer make the best decision, looking at factors in cloud data platform pricing – such as scope, scale, deployment, etc. – and how to determine the ultimate success metric when it comes to making a decision on a cloud data warehouse deployment – price-performance.
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Tags: Big Data, Cloud, Data Center
CLOUD DATABASE PERFORMANCE – MCKNIGHT BENCHMARK REPORT
MCG
April 13, 2020
This third-party report from McKnight Consulting Group uses industry-standard benchmark principles to evaluate the performance of three cloud-optimized analytical platforms architected for the separation of compute and storage – Vertica in Eon Mode, Amazon Redshift, and an unnamed cloud data platform.
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Tags: Big Data, Cloud, Data Center
ENTERPRISE ANALYTIC SOLUTIONS
GigaOm
April 07, 2020
This report is the third in a series of enterprise roadmaps addressing cloud analytic databases. The last two reports focused on comparing vendors on key decision criteria that were targeted primarily at cloud integration. This report is an update to the 2019 Enterprise Roadmap: Cloud Analytic Databases. However, this time around we have new vendors and a new name. We’ve reviewed and adjusted our inclusion criteria. We’re now targeting the technologies that tackle the objectives of an analytics program, as opposed to the means by which they are achieving these objectives.
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Tags: Big Data, Cloud, Data Center
HIGH PERFORMANCE API MANAGEMENT TESTING
GigaOm
March 24, 2020
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technology applications. Large companies and complex organizations have turned to APIs for exchanging data to knit these heterogeneous systems together and turn data into a service. In this paper, we reveal the results of performance testing we completed with four full-lifecycle API management platforms.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING
GigaOm
January 13, 2020
This report details the results of a Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), compared:
Microsoft SQL Server 2019 on an Amazon Web Services (AWS) r5a.8xlarge Elastic Cloud Compute (EC2) instance with General Purpose (gp2) volumes
Microsoft SQL Server 2019 on an Azure E32as_v4 Virtual Machine (VM) with P30 Premium Storage drives
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Tags: Big Data, Cloud, Data Center
DELIVERING ON THE VISION OF MLOPS: A MATURITY-BASED APPROACH
GigaOm
August 13, 2019
This report is targeted at Business and IT decision-makers as they look to implement MLOps, which is an approach to deliver Machine Learning- (ML-) based innovation projects. As well as describing how to address the impact of ML across the development cycle, it presents an approach based on maturity levels such that the organization can build on existing progress.
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Tags: Big Data, Cloud, Data Center
MODERNIZING INSURANCE DATA PLATFORMS TO IMPROVE GOVERNANCE AND ENRICH CUSTOMER EXPERIENCE
GigaOm
June 13, 2019
Pekin Insurance is one of the nation’s most successful insurance providers, with combined assets of $2 billion, more than 800 employees, 1,500 agencies, and 8,500 independent agents. Pekin Insurance is on the fast path to a full overhaul and modernization of their data, from the platform, to quality, to governance, to enabling consumers. They have built a 3-year strategy focusing on Data & Analytics and are wrapping up the final year, focused on a robust data layer with a data lake and a data warehouse, on target, on budget, and within scope.
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Tags: Analytics, Big Data, Cloud
EMBEDDED DATABASE PERFORMANCE REPORT 2
MCG
June 06, 2019
Today, to fully harness data to gain a competitive advantage, embedded databases need a high level of performance to provide real-time processing at scale.
See SQLite, the traditional alternative to the file system approach for embedding data management into edge applications and Actian Zen perform.
See for yourself in this benchmark report by McKnight Consulting Group.
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Tags: Big Data, Cloud, Data Center
DATA WAREHOUSE IN THE CLOUD BENCHMARK PRODUCT PROFILE AND EVALUATION: AMAZON REDSHIFT, MICROSOFT AZURE SQL DATA WAREHOUSE, GOOGLE BIGQUERY, AND SNOWFLAKE DATA WAREHOUSE
GigaOm
April 22, 2019
This report outlines the results from the GigaOm Analytic Field Test based on an industry standard TPC Benchmark H (TPC-H)1 to compare Amazon Redshift, Azure SQL Data Warehouse, Google Big Query, and Snowflake Data Warehouse—four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences in the four platforms.
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Tags: Analytics, Big Data, Cloud
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
April 19, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
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Tags: Big Data, Cloud, Data Center
SQL TRANSACTION PROCESSING, PRICE-PERFORMANCE TESTING ONE
GigaOm
April 17, 2019
This report outlines the results from a Transactional Field Test, derived from the industry-standard TPC Benchmark E (TPC-E), to compare two IaaS cloud database offerings:
Microsoft SQL Server on Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instances
Microsoft SQL Server Microsoft on Azure Virtual Machines (VM)
See publication
Tags: Big Data, Cloud, Data Center
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
April 12, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
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Tags: Big Data, Data Center
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
March 14, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
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Tags: Big Data, Cloud, Data Center
MODERNIZING INSURANCE DATA PLATFORMS TO IMPROVE GOVERNANCE AND ENRICH CUSTOMER EXPERIENCE
GigaOm
February 15, 2019
Pekin Insurance is one of the nation’s most successful insurance providers, with combined assets of $2 billion, more than 800 employees, 1,500 agencies, and 8,500 independent agents. Pekin Insurance is on the fast path to a full overhaul and modernization of their data, from the platform, to quality, to governance, to enabling consumers. They have built a 3-year strategy focusing on Data & Analytics and are wrapping up the final year, focused on a robust data layer with a data lake and a data warehouse, on target, on budget, and within scope.
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Tags: Analytics, Big Data, Cloud
CLOUD DATA WAREHOUSE PERFORMANCE TESTING
GigaOm
February 11, 2019
This report focuses on relational analytical databases in the cloud, because deployments are at an all-time high and poised to expand dramatically. This report outlines the results from a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark DS (TPC-DS)1 comparing Amazon Redshift, Azure SQL Data Warehouse, Google BigQuery, and Snowflake Data Warehouse — four relational analytical databases based on scale-out cloud data warehouses and columnar-based database architectures. Despite these similarities, there are some distinct differences between the four platforms.
See publication
Tags: Analytics, Big Data, Cloud
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
February 05, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
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Tags: Analytics, Big Data, Cloud
CLOUD ANALYTICS PERFORMANCE REPORT
Actian
January 15, 2019
This paper specifically compares two fully-managed, cloud-based analytical databases, Actian Avalanche and Amazon Redshift, two relational analytical databases based on massively parallel processing (MPP) and columnar-based database architectures that scale and provide high-speed analytics. It should be noted while our testing measures the cloud-based performance of both offerings, Avalanche, unlike Redshift, is also available as an on-premise offering, Vector. In addition, Vector is available for developers as a free on-premise community edition, as a download with support in both the Amazon Web Services (AWS) and Azure marketplaces with single-click deployment.
See publication
Tags: Analytics, Big Data, Cloud
ANALYST REPORT: API MANAGEMENT BENCHMARK REPORT
GigaOm
December 25, 2018
Application programming interfaces, or APIs, are now a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems within large companies and complex organizations are a vast array of applications and systems, many of which have turned to APIs as the glue to hold these heterogeneous artifacts together.
This report examines the results of a performance benchmark completed with two popular API management solutions: Kong and Apigee—two full life-cycle API management platforms built with scale-out potential and architectures for large scale, high performance deployments. Despite these similarities, there are some distinct differences in the two platforms.
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Tags: Analytics, Big Data, Cloud
ANALYST REPORT: STATE OF DATA WAREHOUSE
GigaOm
October 25, 2018
Table of Contents
1 The Data Warehouse in the Organization
2 Relationships to Other Research Reports
3 The Data Warehouse Database
4 Analytic Store Platform Choices
5 Choosing the Data Warehouse Platform
6 The Cloud Analytic Database
7 Data Warehouse Flavors
7.1 The Customer Experience Transformation Data Warehouse
7.2 The Asset Maximization with IoT Data Warehouse
7.3 The Operational Extension Data Warehouse
7.4 The Risk Management Data Warehouse
7.5 The Finance Modernization Data Warehouse
7.6 The Product Innovation Data Warehouse
8 Key Takeaways
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Tags: Analytics, Big Data, Cloud
EMBEDDED DATABASE PERFORMANCE REPORT 1
MCG
April 12, 2018
This benchmark did a head-to-head comparison of Actian Zen and InfluxDB for IoT time series data, both installed on a Raspberry Pi running Linux ARM/Raspbian using their native APIs (NoSQL).
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Tags: Big Data, Cloud, Data Center
Platforming the Major Analytic Use Cases for Modern Engineering
Dataversity
May 13, 2021
We’ll describe some use cases as examples of a broad range of modern use cases that need a platform. We will describe some popular valid technology stacks that enterprises use in accomplishing these modern use cases of customer churn, predictive analytics, fraud detection, and supply chain management.
In many industries, to achieve top-line growth, it is imperative that companies get the most out of existing customer relationships. Customer churn use cases are about generating high levels of profitable customer satisfaction through the use of knowledge generated from corporate and external data to help drive a more positive customer experience (CX).
Many organizations are turning to predictive analytics to increase their bottom line and efficiency and, therefore, competitive advantage. It can make the difference between business success or failure.
Fraudulent activity detection is exponentially more effective when risk actions are taken immediately (i.e., stop the fraudulent transaction), instead of after the fact. Fast digestion of a wide network of risk exposures across the network is required in order to minimize adverse outcomes.
Supply chain leaders are under constant pressure to reduce overall supply chain management (SCM) costs while maintaining a flexible and diverse supplier ecosystem. They will leverage IoT, sensors, cameras, and blockchain. Major investments in advanced analytics, warehouse relocation, and automation, both in distribution centers and stores, will be essential for survival.
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Tags: Analytics, Big Data, Cloud
High Performance Cloud Data Warehouse Vendor Evaluation
GigaOm
April 09, 2021
This free 1-hour webinar brings GigaOm analyst William McKnight and special guest, Cloudera’s Bill Zhang, Director of Data Warehouse Product Management to discuss the intriguing results from an in-depth Analytic Field Test derived from the industry-standard TPC-DS benchmark to compare leading cloud data warehouse offerings: Amazon Redshift, Azure Synapse, Snowflake, Google BigQuery and Cloudera Data Warehouse.
Data-driven organizations rely on analytic databases to load, store, and analyze volumes of data at high-speed to derive timely insights. Data volumes within modern organization’s information ecosystems are rapidly expanding—placing significant demands on legacy architectures. Today, to fully harness their data to gain a competitive advantage, businesses need modern, scalable architectures and high levels of performance and reliability to provide timely analytical insights. Companies are attracted to fully-managed cloud services.
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Tags: Analytics, Big Data, Cloud
How To Reduce Your Total Cost of Ownership for Cassandra
DataStax
April 06, 2021
Everybody wants data without limits - infinite scale, zero-downtime and software velocity without going over budget. The weapon of choice is Apache Cassandra, but how do you control data costs and complexity without sacrificing performance? The answer to this is serverless Cassandra! No more nodes, no more servers, no more idle/wasted capacity.
Join us as GigaOm presents the results of their study that empirically validates how serverless Cassandra saved 76% on TCO compared with self-managed Cassandra. Learn:
How to model expected costs of Cassandra workloads
How serverless Cassandra reduces infrastructure and operational costs
What are the criteria and tradeoffs for migration decisions?
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Tags: Analytics, Big Data, Cloud
High Performance Cloud Data Warehouse Vendor Evaluation
GigaOm
March 24, 2021
This free 1-hour webinar brings GigaOm analyst William McKnight and special guest, Cloudera’s Bill Zhang, Director of Data Warehouse Product Management to discuss the intriguing results from an in-depth Analytic Field Test derived from the industry-standard TPC-DS benchmark to compare leading cloud data warehouse offerings: Amazon Redshift, Azure Synapse, Snowflake, Google BigQuery and Cloudera Data Warehouse.
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Tags: Big Data, Cloud, Data Center
Comparing the Enterprise Analytic Solutions
Dataversity
March 11, 2021
Data is the foundation of any meaningful corporate initiative. Fully master the necessary data, and you’re more than halfway to success. That’s why leverageable (i.e., multiple use) artifacts of the enterprise data environment are so critical to enterprise success.
Build them once (keep them updated), and use again many, many times for many and diverse ends. The data warehouse remains focused strongly on this goal. And that may be why, nearly 40 years after the first database was labeled a “data warehouse,” analytic database products still target the data warehouse.
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Tags: Analytics, Big Data, Cloud
Data & Analytics 2021: Defining Trends and Trajectories
Brighttalk
February 24, 2021
Gartner predicts that “by 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling”. In 2020, data analytics has evolved together with AI to produce more accurate predictions and educated suggestions. Join Eric Topham and a panel of industry experts and thought leaders to find out how data and analytics will transform human-machine relationships.
This month's episode of The Business Intelligence Report will look at the defining data and analytics trends to watch in 2021. Some of the topics to be covered during this session will include:
- The growing importance of external data
- Trends of how organizations are finding and using external data
- How data visualization enriches analytics and helps reveal correlations
- The evolution of dashboards. Where are we now and where are we headed?
- Data visualization in real-time for timely, actionable insights
- Visual analytics use cases. Building a data narrative to achieve business results.
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Tags: Analytics, Big Data, Cloud
Increasing Artificial Intelligence Success with Master Data Management
Dataversity
February 11, 2021
Companies all over the world are going through a digital transformation now, which in many cases, is all about maturing the data environment and the use of data. Master data is key to this effort. All transformative projects require master data and usually many subject areas. Current efforts to deliver master data to the enterprise are cumbersome, inefficient, and met with limited acceptance.
We’ll look at enterprise use cases of artificial intelligence and show the master data that is needed. We’ll see what some MDM vendors are doing with AI and how the future of MDM will be shaped by looking at some specific MDM actions influenced by AI.
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Tags: Analytics, Big Data, Cloud
Modernize Data Warehousing: Beyond Performance, the Importance of Other Key Attributes
Vertica
February 02, 2021
Configuration, management, tuning and other tasks can take away from valuable time spent on business analytics. If a platform leads to coding workarounds, non-intuitive implementations and other problems, it can make a big impact on long-term resource usage and cost. A lot of enterprise analytics platform evaluations focus on query price-performance to the exclusion of other features that can have a huge impact on business value, and can cause major headaches if you don’t take them into consideration.
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Tags: Analytics, Big Data, Cloud
2021 Trends in Enterprise Analytics
Vertica
January 14, 2021
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed, and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the third year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
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Tags: Analytics, Big Data, Cloud
Why Organizations Don’t Change When They Need To
Dataversity
January 12, 2021
So you have a great idea for the data in your organization. Maybe it’s been acknowledged by some prominent leaders, but nothing ever happens. When the speaker has done his Action Plans for organizations over the years, he’s heard more questions from clients directed elsewhere in the organization about how to get the initiatives moving than he has heard about the initiatives he is creating. Organizations are mostly not good at moving good ideas forward.
Why does this happen and what can be done about it? The speaker will share his experience with utilizing his favorite skill – getting things done in enterprises.
Dislodge the logjams, make data a key asset, and make your organization an attractive, progressive place for data talent in 2021.
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Tags: Analytics, Big Data, Cloud
Thriving in the Data Age
Brighttalk
January 12, 2021
According to a recent survey, two-thirds of organisations are expecting the value and amount of data to grow almost 5x by 2025. The ‘Data Age’ is here to stay, and the way that we prepare now and the actions we take today will impact our ability to thrive. Embracing technologies like 5G, IoT, blockchain and edge computing, will increase the volume of data produced, and the ways in which data can be used productively to transform business strategy.
Join us in this final episode as we discuss:
- How cloud both fuels the ‘Data Age’ and can help navigate it
- How different industries, including retail, healthcare, finserv, manufacturing and the private sector are embracing the ‘Data Age’
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Tags: Analytics, Big Data, Cloud
Data Lineage and Its Contribution to Governance and Organizational Imperatives
Manta
January 07, 2021
How to assess an organization’s information management level
What the winning approaches to data maturity are
How data lineage contributes to accountable data governance in an organization
How various data roles in an organization benefit from using lineage and use it for various tasks and projects (data governance, impact and root-cause analyses, data quality, audits, and more)
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Tags: Analytics, Big Data, Cloud
Enterprise Analytic Solutions 2021 v4.0
Need a Scale-Out Database?
Integrating Hadoop
Information Management: Strategies for Gaining a Competitive Advantage with Data (The Savvy Manager's Guides)
The Evolution of the Data Platform and What It Means to Data Warehousing
