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Exam Code: P2050-003 Practice exam 2022 by Killexams.com team
IBM Commerce Solutions Selling Technical Mastery Test v1
IBM Solutions approach
Killexams : IBM Solutions approach - BingNews https://killexams.com/pass4sure/exam-detail/P2050-003 Search results Killexams : IBM Solutions approach - BingNews https://killexams.com/pass4sure/exam-detail/P2050-003 https://killexams.com/exam_list/IBM Killexams : IBM's Expertise Nurturing Transformational Change in Fintech

A consultancy business is only as good as the knowhow it can impart onto clients. So it speaks volumes that, when asked what sets IBM Consulting apart, Lee-Han Tjioe, General Manager for Hong Kong and Macau, points to its rich and varied expertise.

“We have both business consulting and technology consulting in our scope,” Lee-Han says. “We have business consultants in our team that help clients with their strategy, with their new propositions, with defining or optimising business processes. That's one part of our practice. The other part is where we also advise on specific technology topics. So we have consultants that are very specialised in key technologies like AI and Hybrid Cloud that can help clients to achieve technology enabled major operational improvements. We basically have both deep business and technology skill sets to deliver end-to-end solutions.”

IBM has been a trusted advisory and delivery partner with high market reputation for decades, and has further developed into an eco-system provider with accurate major corporate acquisitions to expand its AI and Hybrid Cloud skill sets to support clients with implementing differentiating industry and technology solutions. Today, IBM works closely and collaboratively with companies and eco-system partners to achieve required business model changes enabled by modern digital solutions which, without reliable partners, would be hard to scale at fast pace.

In many cases, IBM’s clients are international and local conglomerate companies across multiple key industries. “We are co-creating with our clients and ecosystem partners to develop new propositions and experiences, and applying best practices in a fast fashion with fast go-to-market. One example is with an insurance company that we work with on IOT for “pay-how-you-drive” insurance. And so we helped the client to actually get the right technologies into the cars to track driving behaviours and attach that to very innovative insurance propositions.”

IBM’s partnership with AXA

Another example is IBM’s strong partnership with insurance company AXA, which has endured for many years. Initially, AXA had their applications managed by providers over the world but was looking to consolidate, recognising that it was very hard to achieve consistent levels of service as well as cost-effectiveness. AXA brought IBM on board to manage those applications but also to help them innovate.

“Our partnership with AXA means that we are delivering multi-year support for the business-critical applications that AXA has,” Lee-Han continues. “Those applications are supporting distribution, sales, and key internal operations. We have transferred knowledge of 60 applications within four months and now support about 100+ applications. This is the foundation for our partnership with AXA. We are now helping with further accelerated0 deployment of API-based services on AXA’s digital platform to meet the fast developing new market needs.”

IBM Consulting and Our Transformation

IBM Consulting’s business can be broken down into four pillars: 1. Strategy Consulting, where it works with clients to define vision and blueprint for its future; 2. Experience Consulting, where Garage and Design thinking approaches are applied to redefine new experiences for clients and their customers; 3. Operations Consulting, in which it examines how it can optimise current business activity with automation and new technologies such as AI and IoT; and lastly 4. Technology Consulting, where IBM helps clients to implement or manage enterprise solutions and leverage Cloud technologies for optimising application management. 

It’s a diverse remit – but at the heart of everything the firm does is the Virtual Enterprise, IBM’s framework that helps clients in their pursuit of digital transformation. Transformation is not just about taking on technical hurdles, IBM’s depth of transformation experiences and understanding of key industry opportunities proofs a Virtual Enterprise approach can be achieved with an end-to-end vision for achieving business growth.

READ THE FULL AXA HONG KONG REPORT HERE

Tue, 12 Jul 2022 18:39:00 -0500 en text/html https://fintechmagazine.com/articles/ibms-expertise-nurturing-transformational-change-in-fintech
Killexams : IBM’s human-centered approach is the only big tech blueprint AI startups should follow

IBM’s gone by just its initials for so long that many of us have to stop and think about what the letters stand for. International Business Machines.

I was reminded of the corporation’s singular focus last week during the TNW 2022 Conference when Seth Dobrin, IBM’s first chief AI officer, took the stage to talk about artificial intelligence.

As Dobrin put it, IBM “doesn’t do consumer AI.” You won’t be downloading IBM’s virtual assistant for your smart phone anytime soon. Big Blue won’t be getting into the selfie app AI filter game.

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Simply put, IBM’s here to provide value for its clients and partners and to create AI models that make human lives easier, better, or both.

That’s all pretty easy to say. But how does a company that’s not focused on creating products and services for the individual consumer actually walk that kind of talk?

According Dobrin, it’s not hard: care about how individual humans will be affected by the models you monetize:

We’re very stringent about the type of data we will ingest and make money from.

During a discussion with the Financial Times’ Tim Bradshaw during the conference, Dobrin used the example of large-parameter models such as GPT-3 and DALL-E 2 as a way to describe IBM’s approach.

He described those models as “toys,” and for good reason: they’re fun to play with, but they’re ultimately not very useful. They’re prone to unpredictability in the form of nonsense, hate-speech, and the potential to output private personal information. This makes them dangerous to deploy outside of laboratories.

However, Dobrin told Bradshaw and the audience that IBM was also working on a similar system. He referred to these agents as “foundational models,” meaning they can be used for multiple applications once developed and trained.

The IBM difference, however, is that the company is taking a human-centered approach to the development of its foundational models.

Under Dobrin’s leadership, the company’s cherry-picking datasets from a variety of sources and then applying internal terms and conditions to them prior to their integration into models or systems.

It’s one thing if GPT-3 accidentally spits out something offensive, these kinds of things are expected in laboratories. But it’s an entirely different situation when, as a hypothetical example, a bank’s production language model starts outputting nonsense or private information to customers.

Luckily, IBM (a company that works with corporations across a spectrum of industries including banking, transportation, and energy) doesn’t believe in cramming a giant database of unchecked data into a model and hoping for the best.

Which brings us to what’s perhaps the most interesting take away from Dobrin’s chat with Bradshaw: “be ready for regulations.”

As the old saying goes: BS in, BS out. If you’re not in control of the data you’re training with, life’s going to get hard for your AI startup come regulation time.

And the Wild West of AI acquisitions is going to come to an end soon as more and more regulatory bodies seek to protect citizens from predatory AI companies and corporate overreach.

If your AI startup creates models that won’t or can’t be compliant in time for use in the EU or US once the regulation hammers fall, your chances of selling them to or getting acquired by a corporation that does business internationally are slim to none.

No matter how you slice it, IBM’s an outlier. It and Dobrin apparently relish the idea of delivering compliance-ready solutions that help protect people’s privacy.

While the rest of big tech spends billions of dollars building eco-harming models that serve no purpose other than to pass arbitrary benchmarks, IBM’s more panic about outcomes than speculation.

And that’s just weird. That’s not how the majority of the industry does business.

IBM and Dobrin are trying to redefine what big tech’s position in the AI sector is. And, it turns out, when your bottom line isn’t driven by advertising revenue, subscriber numbers, or future hype, you can build solutions that are as efficacious as they are ethical.

And that leaves the vast majority of people in the AI startup world with some questions to answer.

Is your startup ready for the future? Are you training models ethically, considering human outcomes, and able to explain the biases baked into your systems? Can your models be made GDPR, EU AI, and Illinois BIPA compliant?

If the current free-for-all dies out and VCs stop throwing money at prediction models and other vaporware or prestidigitation-based products, can your models still provide business value?

There’s probably still a little bit of money to be made for companies and startups who leap aboard the hype train, but there’s arguably a whole lot more to be made for those whose products can actually withstand an AI winter.

Human-centered AI technologies aren’t just a good idea because they make life better for humans, they’re also the only machine learning applications worth betting on over the long haul.

When the dust settles, and we’re all less impressed by the prestidigitation and parlor tricks that big tech’s spending billions of dollars on, IBM will still be out here using our planet’s limited energy resources to develop solutions with individual human outcomes in mind.

That’s the very definition of “sustainability,” and why IBM’s poised to become the defacto technological leader in the global artificial intelligence community under Dobrin’s so-far expert leadership.

Mon, 20 Jun 2022 09:57:00 -0500 en text/html https://thenextweb.com/news/ibms-human-centered-approach-is-the-only-big-tech-blueprint-ai-startups-should-follow
Killexams : Top 10 data lake solution vendors in 2022

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As the world becomes increasingly data-driven, businesses must find suitable solutions to help them achieve their desired outcomes. Data lake storage has garnered the attention of many organizations that need to store large amounts of unstructured, raw information until it can be used in analytics applications.

The data lake solution market is expected to grow rapidly in the coming years and is driven by vendors that offer cost-effective, scalable solutions for their customers.

Learn more about data lake solutions, what key features they should have and some of the top vendors to consider this year. 

What is a data lake solution?

A data lake is defined as a single, centralized repository that can store massive amounts of unstructured and semi-structured information in its native, raw form. 

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It’s common for an organization to store unstructured data in a data lake if it hasn’t decided how that information will be used. Some examples of unstructured data include images, documents, videos and audio. These data types are useful in today’s advanced machine learning (ML) and advanced analytics applications.

Data lakes differ from data warehouses, which store structured, filtered information for specific purposes in files or folders. Data lakes were created in response to some of the limitations of data warehouses. For example, data warehouses are expensive and proprietary, cannot handle certain business use cases an organization must address, and may lead to unwanted information homogeneity.

On-premise data lake solutions were commonly used before the widespread adoption of the cloud. Now, it’s understood that some of the best hosts for data lakes are cloud-based platforms on the edge because of their inherent scalability and considerably modular services. 

A 2019 report from the Government Accountability Office (GAO) highlights several business benefits of using the cloud, including better customer service and the acquisition of cost-effective options for IT management services.

Cloud data lakes and on-premise data lakes have pros and cons. Businesses should consider cost, scale and available technical resources to decide which type is best.

Read more about data lakes: What is a data lake? Definition, benefits, architecture and best practices

5 must-have features of a data lake solution

It’s critical to understand what features a data lake offers. Most solutions come with the same core components, but each vendor may have specific offerings or unique selling points (USPs) that could influence a business’s decision.

Below are five key features every data lake should have:

1. Various interfaces, APIs and endpoints

Data lakes that offer diverse interfaces, APIs and endpoints can make it much easier to upload, access and move information. These capabilities are important for a data lake because it allows unstructured data for a wide range of use cases, depending on a business’s desired outcome.

2. Support for or connection to processing and analytics layers

ML engineers, data scientists, decision-makers and analysts benefit most from a centralized data lake solution that stores information for easy access and availability. This characteristic can help data professionals and IT managers work with data more seamlessly and efficiently, thus improving productivity and helping companies reach their goals.

3. Robust search and cataloging features

Imagine a data lake with large amounts of information but no sense of organization. A viable data lake solution must incorporate generic organizational methods and search capabilities, which provide the most value for its users. Other features might include key-value storage, tagging, metadata, or tools to classify and collect subsets of information.

4. Security and access control

Security and access control are two must-have features with any digital tool. The current cybersecurity landscape is expanding, making it easier for threat actors to exploit a company’s data and cause irreparable damage. Only certain users should have access to a data lake, and the solution must have strong security to protect sensitive information.

5. Flexibility and scalability

More organizations are growing larger and operating at a much faster rate. Data lake solutions must be flexible and scalable to meet the ever-changing needs of modern businesses working with information.

Also read: Unlocking analytics with data lake and graph analysis

Top 10 data lake solution vendors in 2022

Some data lake solutions are best suited for businesses in certain industries. In contrast, others may work well for a company of a particular size or with a specific number of employees or customers. This can make choosing a potential data lake solution vendor challenging. 

Companies considering investing in a data lake solution this year should check out some of the vendors below.

1. Amazon Web Services (AWS)

The AWS Cloud provides many essential tools and services that allow companies to build a data lake that meets their needs. The AWS data lake solution is widely used, cost-effective and user-friendly. It leverages the security, durability, flexibility and scalability that Amazon S3 object storage offers to its users. 

The data lake also features Amazon DynamoDB to handle and manage metadata. AWS data lake offers an intuitive, web-based console user interface (UI) to manage the data lake easily. It also forms data lake policies, removes or adds data packages, creates manifests of datasets for analytics purposes, and features search data packages.

2. Cloudera

Cloudera is another top data lake vendor that will create and maintain safe, secure storage for all data types. Some of Cloudera SDX’s Data Lake Service capabilities include:

  • Data schema/metadata information
  • Metadata management and governance
  • Compliance-ready access auditing
  • Data access authorization and authentication for improved security

Other benefits of Cloudera’s data lake include product support, downloads, community and documentation. GSK and Toyota leveraged Cloudera’s data lake to garner critical business intelligence (BI) insights and manage data analytics processes.

3. Databricks 

Databricks is another viable vendor, and it also offers a handful of data lake alternatives. The Databricks Lakehouse Platform combines the best elements of data lakes and warehouses to provide reliability, governance, security and performance.

Databricks’ platform helps break down silos that normally separate and complicate data, which frustrates data scientists, ML engineers and other IT professionals. Aside from the platform, Databricks also offers its Delta Lake solution, an open-format storage layer that can Strengthen data lake management processes. 

4. Domo

Domo is a cloud-based software company that can provide big data solutions to all companies. Users have the freedom to choose a cloud architecture that works for their business. Domo is an open platform that can augment existing data lakes, whether it’s in the cloud or on-premise. Users can use combined cloud options, including:

  • Choosing Domo’s cloud
  • Connecting to any cloud data
  • Selecting a cloud data platform

Domo offers advanced security features, such as BYOK (bring your own key) encryption, control data access and governance capabilities. Well-known corporations such as Nestle, DHL, Cisco and Comcast leverage the Domo Cloud to better manage their needs.

5. Google Cloud

Google is another big tech player offering customers data lake solutions. Companies can use Google Cloud’s data lake to analyze any data securely and cost-effectively. It can handle large volumes of information and IT professionals’ various processing tasks. Companies that don’t want to rebuild their on-premise data lakes in the cloud can easily lift and shift their information to Google Cloud. 

Some key features of Google’s data lakes include Apache Spark and Hadoop migration, which are fully managed services, integrated data science and analytics, and cost management tools. Major companies like Twitter, Vodafone, Pandora and Metro have benefited from Google Cloud’s data lakes.

6. HP Enterprise

Hewlett Packard Enterprise (HPE) is another data lake solution vendor that can help businesses harness the power of their big data. HPE’s solution is called GreenLake — it offers organizations a truly scalable, cloud-based solution that simplifies their Hadoop experiences. 

HPE GreenLake is an end-to-end solution that includes software, hardware and HPE Pointnext Services. These services can help businesses overcome IT challenges and spend more time on meaningful tasks. 

7. IBM

Business technology leader IBM also offers data lake solutions for companies. IBM is well-known for its cloud computing and data analytics solutions. It’s a great choice if an operation is looking for a suitable data lake solution. IBM’s cloud-based approach operates on three key principles: embedded governance, automated integration and virtualization.

These are some data lake solutions from IBM: 

  • IBM Db2
  • IBM Db2 BigSQL
  • IBM Netezza
  • IBM Watson Query
  • IBM Watson Knowledge Catalog
  • IBM Cloud Pak for Data

With so many data lakes available, there’s surely one to fit a company’s unique needs. Financial services, healthcare and communications businesses often use IBM data lakes for various purposes.

8. Microsoft Azure

Microsoft offers its Azure Data Lake solution, which features easy storage methods, processing, and analytics using various languages and platforms. Azure Data Lake also works with a company’s existing IT investments and infrastructure to make IT management seamless.

The Azure Data Lake solution is affordable, comprehensive, secure and supported by Microsoft. Companies benefit from 24/7 support and expertise to help them overcome any big data challenges they may face. Microsoft is a leader in business analytics and tech solutions, making it a popular choice for many organizations.

9. Oracle

Companies can use Oracle’s Big Data Service to build data lakes to manage the influx of information needed to power their business decisions. The Big Data Service is automated and will provide users with an affordable and comprehensive Hadoop data lake platform based on Cloudera Enterprise. 

This solution can be used as a data lake or an ML platform. Another important feature of Oracle is it is one of the best open-source data lakes available. It also comes with Oracle-based tools to add even more value. Oracle’s Big Data Service is scalable, flexible, secure and will meet data storage requirements at a low cost.

10. Snowflake

Snowflake’s data lake solution is secure, reliable and accessible and helps businesses break down silos to Strengthen their strategies. The top features of Snowflake’s data lake include a central platform for all information, fast querying and secure collaboration.

Siemens and Devon Energy are two companies that provide testimonials regarding Snowflake’s data lake solutions and offer positive feedback. Another benefit of Snowflake is its extensive partner ecosystem, including AWS, Microsoft Azure, Accenture, Deloitte and Google Cloud.

The importance of choosing the right data lake solution vendor 

Companies that spend extra time researching which vendors will offer the best enterprise data lake solutions for them can manage their information better. Rather than choose any vendor, it’s best to consider all options available and determine which solutions will meet the specific needs of an organization.

Every business uses information, some more than others. However, the world is becoming highly data-driven — therefore, leveraging the right data solutions will only grow more important in the coming years. This list will help companies decide which data lake solution vendor is right for their operations.

Read next: Get the most value from your data with data lakehouse architecture

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Fri, 15 Jul 2022 09:40:00 -0500 Shannon Flynn en-US text/html https://venturebeat.com/2022/07/15/top-10-data-lake-solution-vendors-in-2022/
Killexams : IBM Aims to Capture Growing Market Opportunity for Data Observability with Databand.ai Acquisition

Acquisition helps enterprises catch "bad data" at the source

Extends IBM's leadership in observability to the full stack of capabilities for IT -- across infrastructure, applications, data and machine learning

ARMONK, N.Y., July 6, 2022  /CNW/ -- IBM (NYSE: IBM) today announced it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures and poor quality — before it impacts their bottom-line. Today's news further strengthens IBM's software portfolio across data, AI and automation to address the full spectrum of observability and helps businesses ensure that trustworthy data is being put into the right hands of the right users at the right time.

Databand.ai is IBM's fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities. IBM has acquired more than 25 companies since Arvind Krishna became CEO in April 2020.

As the volume of data continues to grow at an unprecedented pace, organizations are struggling to manage the health and quality of their data sets, which is necessary to make better business decisions and gain a competitive advantage. A rapidly growing market opportunity, data observability is quickly emerging as a key solution for helping data teams and engineers better understand the health of data in their system and automatically identify, troubleshoot and resolve issues, like anomalies, breaking data changes or pipeline failures, in near real-time. According to Gartner, every year poor data quality costs organizations an average $12.9 million. To help mitigate this challenge, the data observability market is poised for strong growth.1

Data observability takes traditional data operations to the next level by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist. When combined with a full stack observability strategy, it can help IT teams quickly surface and resolve issues from infrastructure and applications to data and machine learning systems.

Databand.ai's open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure. This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack. Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.

The acquisition of Databand.ai builds on IBM's research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.

For example, Databand.ai capabilities can alert data teams and engineers when the data they are using to fuel an analytics system is incomplete or missing. In common cases where data originates from an enterprise application, Instana can then help users quickly explain exactly where the missing data originated from and why an application service is failing. Together, Databand.ai and IBM Instana provide a more complete and explainable view of the entire application infrastructure and data platform system, which can help organizations prevent lost revenue and reputation.

"Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don't have access to the data they need in any given moment, their business can grind to a halt," said Daniel Hernandez, General Manager for Data and AI, IBM. "With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale."

Data observability solutions are also a key part of an organization's broader data strategy and architecture. The acquisition of Databand.ai further extends IBM's existing data fabric solution  by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time – no matter where it resides.

"You can't protect what you can't see, and when the data platform is ineffective, everyone is impacted –including customers," said Josh Benamram, Co-Founder and CEO, Databand.ai. "That's why global brands such as FanDuel, Agoda and Trax Retail already rely on Databand.ai to remove bad data surprises by detecting and resolving them before they create costly business impacts. Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients."

Headquartered in Tel Aviv, Israel, Databand.ai employees will join IBM Data and AI, further building on IBM's growing portfolio of Data and AI products, including its IBM Watson capabilities and IBM Cloud Pak for Data. Financial details of the deal were not disclosed. The acquisition closed on June 27, 2022.

To learn more about Databand.ai and how this acquisition enhances IBM's data fabric solution and builds on its full stack of observability software, you can read our blog about the news or visit here: https://www.ibm.com/analytics/data-fabric.

About Databand.ai

Databand.ai is a product-driven technology company that provides a proactive data observability platform, which empowers data engineering teams to deliver reliable and trustworthy data. Databand.ai removes bad data surprises such as data incompleteness, anomalies, and breaking data changes by detecting and resolving issues before they create costly business impacts. Databand.ai's proactive approach ties into all stages of your data pipelines, beginning with your source data, through ingestion, transformation, and data access. Databand.ai serves organizations throughout the globe, including some of the world's largest companies in entertainment, technology, and communications. Our focus is on enabling customers to extract the maximum value from their strategic data investments. Databand.ai is backed by leading VCs Accel, Blumberg Capital, Lerer Hippeau, Differential Ventures, Ubiquity Ventures, Bessemer Venture Partners, Hyperwise, and F2. To learn more, visit www.databand.ai.

About IBM

IBM is a leading global hybrid cloud and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,800 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently, and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM's legendary commitment to trust, transparency, responsibility, inclusivity, and service. For more information, visit www.ibm.com.

Media Contact:
Sarah Murphy
IBM Communications
[email protected]

1 [1] Source: Smarter with Gartner, "How to Strengthen Your Data Quality," Manasi Sakpal, [July 14, 2021]

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

SOURCE IBM

Wed, 06 Jul 2022 00:00:00 -0500 en text/html https://www.newswire.ca/news-releases/ibm-aims-to-capture-growing-market-opportunity-for-data-observability-with-databand-ai-acquisition-808040023.html
Killexams : IBM Acquires Israeli Data Observability Startup Databand.ai

American tech giant IBM announced on Wednesday that it had acquired its acquisition of Tel-Aviv-based company Databand.ai, a data observability software company that helps organizations with data issues.

Databand.ai works to help companies alleviate data errors, pipeline failures, and poor data quality before the company’s bottom line is impacted. By acquiring Databand.ai, IBM hopes to strengthen its software portfolio across artificial intelligence, data, and automation, ultimately ensuring data stays secure at all times.

Founded in 2018 by CEO Josh Benamram, Victor Shafran, and CTO Evgeny Shulman, Databand.ai has developed a unified data pipeline observability solution that’s built for data engineers.

Databand.ai has an open and extendable approach that allows data engineering teams to easily integrate and gain observability into their data infrastructure. In partnering with IBM, Databand.ai will be able to expand its data integration capabilities to meet the needs of more commercial data solutions. IBM will also benefit from the acquisition, as Databand.ai’s software will partner with IBM Observability by Instana APM and IBM Watson Studio in addressing the full spectrum of observability across information technologies.

Databand.ai marks IBM’s fifth acquisition in 2022. 

IBM’s acquisition comes at a time when during which the volume of data is growing at an unprecedented rate. Now more than ever, organizations are grappling with the challenges of managing healthy and high-quality data sets. Data observability is newly emerging as a prime solution for helping companies and engineers understand the status of their data and efficiently address and troubleshoot issues as they arise.

“Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don’t have access to the data they need in any given moment, their business can grind to a halt,” said Daniel Hernandez, general manager for Data and AI, IBM. 

“With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data, and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale,” he added.  

Thu, 07 Jul 2022 08:10:00 -0500 en-US text/html https://nocamels.com/2022/07/ibm-databand-data-observability/
Killexams : IBM acquires Databand.ai No result found, try new keyword!IBM recently announced it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including ... Sat, 16 Jul 2022 04:04:00 -0500 en-ph text/html https://www.msn.com/en-ph/news/money/ibm-acquires-databandai/ar-AAZE6QG Killexams : InterPro Grows Q2 Bookings, Named One of 10 IBM Solution Providers to Watch in 2022

Press release content from Globe Newswire. The AP news staff was not involved in its creation.

STONEHAM, Mass., July 12, 2022 (GLOBE NEWSWIRE) -- InterPro Solutions, which offers the first and only suite of mobile solutions designed exclusively for IBM Maximo®, announced today that Q2 was another successful quarter, improving sales bookings by more than 50 percent over Q1, and was selected by CIOCoverage to its list of 10 IBM Solution Providers to Watch in 2022.

IBM Maximo is the top enterprise asset management (EAM) software in the world, used by millions of operations and maintenance professionals to manage complex facilities and field environments. InterPro offers a suite of mobile apps built exclusively for Maximo that O&M teams need to do their jobs efficiently and effectively without the cost, complexity, and service impacts of available alternatives.

In Q2, InterPro improved year-over-year bookings by over 13 percent as compared to Q2 2021, and more than 50 percent over Q1 2022. Over the period, InterPro added a number of innovative organizations to its client list, including a major theme park and an Ivy League medical school. InterPro also saw expansions at current clients Maryland Department of Transportation, Duke Energy, Hammerhead Resources, EQT Corporation, West Fraser, Hong Kong Jockey Club, and Maricopa County, among others. For the sixth straight quarter, the company’s sales pipeline increased to a new high.

A number of bookings were for a 2021 addition to the EZMax Suite, EZMaxVendor. EZMaxVendor is a cloud solution that enables organizations to manage and schedule external service vendors like they’re an extension of their internal workforce. It eliminates surprises by establishing a shared understanding on work scope, cost, location, start time, and technicians, and automatically saves all work execution details to the organization’s Enterprise Asset Management (EAM) system.

“We went into Q2 with high expectations. Driven by expanded EZMaxMobile footprints at a number of existing clients and continued success with our newer products, we increased our sales by more than 50 percent over Q1 and again saw expansion of our sales pipeline to an all-time high,” said Dan Smith, Vice President, Sales and Marketing at InterPro Solutions.

In April, InterPro announced it was selected by CIOCoverage to its list of 10 IBM Solution Providers to Watch in 2022. CIOCoverage helps CEOs, CXOs, and CIOs stay aware and abreast of all the latest digital advancements and technological surges, helping their organizations effectively respond to client expectations and evolve their digital technologies and processes. Its 10 IBM Solution Providers to Watch in 2022 Special Edition highlights a select list of IBM business partners that are leading that digital advancement.

CIOCoverage described InterPro’s EZMax Suite for IBM Maximo as having “accessible, understandable interfaces, vibrant visuals, and robust functionality allowing for maintenance managers and technicians to work efficiently and effectively.” They continued, “Offering the first and only suite of mobile Enterprise Asset Management (EAM) applications built specifically for IBM Maximo, InterPro Solutions leverages native Maximo rules and permissions, and even extends native Maximo capabilities to reflect how people carry out their work activities.”

“InterPro has developed a suite of Maximo mobile products with unparalleled performance and unmatched mobile functionality,” said Bill Fahey, InterPro Solutions’ Chief Executive Officer. “Our efforts resulted in new clients across a variety of industries, an expanded footprint across many existing clients and industry recognition by CIOCoverage. Having increased our sales bookings by more than 50 percent over Q1 while continuing to grow our sales pipeline, we’re very bullish about the remainder of 2022.”

To learn more about InterPro’s EZMax Suite for Maximo, visit https://interprosoft.com/ezmax-suite/

About InterPro Solutions
InterPro Solutions, an IBM Business Partner, offers the first and only suite of mobile Enterprise Asset Management (EAM) solutions designed exclusively for IBM Maximo – using native Maximo rules, permissions and datastores – eliminating double updates, data lags, and synchronization failures. InterPro’s EZMax Suite expands upon native Maximo capabilities to mirror the way people actually work – with intuitive navigation, rapid app response, and rich functionality – allowing operations and maintenance professionals to effectively communicate with their community members and manage tasks, technicians, and vendors in a way that improves responsiveness to their organizations. To learn more, visit interprosoft.com.

Media contact: Melissa Tyler mtyler@interprosoft.com 781-213-1166

Tue, 12 Jul 2022 01:03:00 -0500 en text/html https://apnews.com/press-release/GlobeNewswire/asset-management-6af54141666d095be32ac0fc72e574aa
Killexams : IBM Eyes Data Observability Market with Databand.ai Acquisition

IBM today announced it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures and poor quality — before it impacts their bottom-line.

The acquisition will further strengthens IBM’s software portfolio across data, AI and automation to address the full spectrum of observability and helps businesses ensure that trustworthy data is being put into the right hands of the right users at the right time.

IBM seems to be on an acquisition spree this year.  Let it be noted that Databand.ai becomes IBM’s fifth acquisition in 2022, as the company continues to bolster its hybrid cloud and AI skills and capabilities. IBM has acquired more than 25 companies since Arvind Krishna became CEO in April 2020.

As the volume of data continues to grow at an unprecedented pace, organizations are struggling to manage the health and quality of their data sets, which is necessary to make better business decisions and gain a competitive advantage. A rapidly growing market opportunity, data observability is quickly emerging as a key solution for helping data teams and engineers better understand the health of data in their system and automatically identify, troubleshoot and resolve issues, like anomalies, breaking data changes or pipeline failures, in near real-time. According to Gartner, every year poor data quality costs organizations an average $12.9 million. To help mitigate this challenge, the data observability market is poised for strong growth.

Data observability takes traditional data operations to the next level by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist. When combined with a full stack observability strategy, it can help IT teams quickly surface and resolve issues from infrastructure and applications to data and machine learning systems.

Databand.ai’s open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure. This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack. Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.

The acquisition of Databand.ai builds on IBM’s research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.

For example, Databand.ai capabilities can alert data teams and engineers when the data they are using to fuel an analytics system is incomplete or missing. In common cases where data originates from an enterprise application, Instana can then help users quickly explain exactly where the missing data originated from and why an application service is failing. Together, Databand.ai and IBM Instana provide a more complete and explainable view of the entire application infrastructure and data platform system, which can help organizations prevent lost revenue and reputation.

“Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don’t have access to the data they need in any given moment, their business can grind to a halt,” said Daniel Hernandez, General Manager for Data and AI, IBM. “With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale.”

Data observability solutions are also a key part of an organization’s broader data strategy and architecture. The acquisition of Databand.ai further extends IBM’s existing data fabric solution  by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time – no matter where it resides.

“You can’t protect what you can’t see, and when the data platform is ineffective, everyone is impacted –including customers,” said Josh Benamram, Co-Founder and CEO, Databand.ai. “That’s why global brands such as FanDuel, Agoda and Trax Retail already rely on Databand.ai to remove bad data surprises by detecting and resolving them before they create costly business impacts. Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients.”

Headquartered in Tel Aviv, Israel, Databand.ai employees will join IBM Data and AI, further building on IBM’s growing portfolio of Data and AI products, including its IBM Watson capabilities and IBM Cloud Pak for Data. Financial details of the deal were not disclosed. The acquisition closed on June 27, 2022.

The acquisition of Databand.ai clearly enhances IBM’s data fabric solution and builds on its full stack of observability software.

Thu, 07 Jul 2022 00:46:00 -0500 en-US text/html https://www.smechannels.com/ibm-eyes-data-observability-market-with-databand-ai-acquisition/
Killexams : IBM Acquires Databand.ai To Extend Leadership In Data Observability

IBM has announced that it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures and poor quality — before it impacts their bottom-line. 

The acquisition strengthens IBM's software portfolio across data, AI and automation to address the full spectrum of observability and helps businesses ensure that trustworthy data is being put into the right hands of the right users at the right time.

The financial terms of the deal were not disclosed.

Databand.ai is IBM's fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities. IBM has acquired more than 25 companies since Arvind Krishna became CEO in April 2020.

According to Gartner, every year poor data quality costs organizations an average USD 12.9 million. To help mitigate this challenge, the data observability market is poised for strong growth.

Databand.ai's open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure. This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack. Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.

The acquisition of Databand.ai builds on IBM's research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.

"With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale”, said Daniel Hernandez, General Manager for Data and AI, IBM.


Wed, 06 Jul 2022 12:00:00 -0500 en text/html https://www.businessworld.in/article/IBM-Acquires-Databand-ai-To-Extend-Leadership-In-Data-Observability/07-07-2022-435859/
Killexams : IBM Acquires Databand.ai to Boost Data Observability Capabilities

IBM is acquiring Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures, and poor quality. The acquisition further strengthens IBM's software portfolio across data, AI, and automation to address the full spectrum of observability.

Databand.ai is IBM's fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities.

Databand.ai's open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure.

This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack.

Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.

The acquisition of Databand.ai builds on IBM's research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.

"Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don't have access to the data they need in any given moment, their business can grind to a halt," said Daniel Hernandez, general manager for data and AI, IBM. "With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale."

The acquisition of Databand.ai further extends IBM's existing data fabric solution by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time—no matter where it resides.

Headquartered in Tel Aviv, Israel, Databand.ai employees will join IBM Data and AI, further building on IBM's growing portfolio of Data and AI products, including its IBM Watson capabilities and IBM Cloud Pak for Data. Financial details of the deal were not disclosed. The acquisition closed on June 27, 2022.

For more information about this news, visit www.ibm.com.


Mon, 11 Jul 2022 01:02:00 -0500 en text/html https://www.dbta.com/Editorial/News-Flashes/IBM-Acquires-Databandai-to-Boost-Data-Observability-Capabilities-153842.aspx
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