Driving IT Transformation with Agile Analytics

•Download as PPTX, PDF•

1 like•298 views

Analytics is becoming increasingly important for industrial companies. Solving the data integration challenge is the foundation of an analytics strategy and platform. The integration platform must be versatile in ingesting any data type from any data source of any quality level.

Software

1 Bit Stew Systems Inc. Confidential and Proprietary
Driving IT Transformation with Agile Analytics
By Andrew Miller

Only 18% of survey
respondents has extensively
integrated their analytics
initiatives across operations
and realized objectives.
Capgemini Consulting Digital Transformation Institute
March 2016

3 Bit Stew Systems Inc. Confidential and Proprietary
IT Transformation
• Features to look for in the next generation
of analytics platforms
– Offers internal customers self-service analytics
– De-centralize analytics from the IT organization
closer to the operational end user
• Versatility in ingesting data types from
any source at any quality level
– Real-time data ingestion enabled
– Built to scale

4 Bit Stew Systems Inc. Confidential and Proprietary
Edge Intelligence Makes the Difference
• Ability to integrate data at the edge – close to
the raw data
• Edge capabilities provides a competitive
advantage IT can offer internal customers
• Faster insights in real-time
• Scale and standardize on a single data
ingestion solution Distributed Intelligence that Seamlessly
Collaborates with the Enterprise

The next generation data
integration and analytics
platform should contain a
sophisticated framework
and library of algorithms
and methods.

6 Bit Stew Systems Inc. Confidential and Proprietary
Algorithms for Industrial Enterprise
• A library of algorithms for manufacturing operations might include:
– Outlier detection
• Prevents potential failure of assets
• Detect critical scenarios for plant floor equipment
• Preventative maintenance
– Seasonal decomposition, Smoothing and Clustering
• Planning teams can use this information to efficiently control inventory
• Prioritize capital expansion projects with strong statistical rationale
• Six Sigma analysis

7 Bit Stew Systems Inc. Confidential and Proprietary
Learn more about Bit Stew
Visit www.info.bitstew.com
Follow us on
Download the whitepaper: http://info.bitstew.com/whitepaper-agile-analytics

8 Bit Stew Systems Inc. Confidential and Proprietary
Andrew Miller is an outcome focused sales engineer with over five years
in network consulting, and a decade in in the information technology
industry. Andrew brings experience in international project and program
management and technical team leadership and management. At Bit
Stew, Andrew drives eastern US and European direct technical sales
support activities for the company. Andrew also drives technical activity
within the partner ecosystem development team and is responsible for
partner recruitment, onboarding, and sales support.
About the Author

What's hot

Integris software ppt

integrisus

The iEx.ec Distributed Cloud: Latest Developments and Perspectives

Gilles Fedak

EthCon Korea 28 May 2019

iExec

Cyber crimes are on the rise and especially prevalent during the global pandemic where hackers leverage the vulnerabilities of organisations for new opportunities through technology. Hospitals, for instance, are more likely to pay ransoms to restore access to their servers. Similarly, criminals may believe that corporations grappling with economic turmoil or logistical crises will be similarly easy to manipulate.

Cybersecurity

IndSightsResearchSG

Research Topics in IOT

Techsparks

AI as a Catalyst for IoT

marina romanovich

Why Cisco- for-Intelligence

E.S.G. JR. Consulting, Inc.

Adopting Emerging Technologies

IndSightsResearchSG

Cisco data analytics in ioe_rajiv niles_2015 nov

CiscoKorea

What is Cloud and what are the best practices?

IndSightsResearchSG

Want to be part of the Internet of Things revolution then this session is for you, Microsoft Azure as a platform delivers the capabilities to enable your IoT solution from building blocks through to finished services. In this demonstration rich session you will learn about Microsoft’s position on IoT, and the technology and services being delivered from Microsoft to help you develop, connect, manage and unlock data insights

Internet of things

K.Mohamed Faizal

Az-Internet of things

kaushalkishor94

Fintech Belgium - MeetUp on The Right Tech for your FinTech - Philippe Cornet...

FinTech Belgium

Sect f43

SelectedPresentations

Iot & security automation-by Er. Nashet Ali

Nashet Ali

74.5 billion devices will be connected to the internet by 2025. The Internet of Things (IoT) is going to impact every industry around the world, if it hasn't already. Of course, something as significant as the IoT will present a number of challenges as it is introduced to traditional operations environments. Access this infographic to prepare for an onslaught of IoT use cases and refocus your strategy to focus on scale, complexity, and security.

IoT: 3 keys to handling the oncoming barrage of use cases

Abhishek Sood

Cryptolab Presentation: Crypto Searching Engine

Massimo Bertaccini

Should you connect devices directly to the cloud, or rather consolidate them via a field gateway? Discover the main raisons behind introducing a gateway into your IoT architecture, how they accelerate a rollout and what capabilities should you look for. Learn how gateways cope with connectivity issues and security challenges. Discover from Sam’s experiences how crucial IoT field gateways are for the future roadmap of your IoT solution. Being a connected company is no small decision. But you can make it easy;

The truth about IoT field gateways (Sam Vanhoutte @IoT Convention Europe 2017)

Codit

How I started with Azure IoT - Global Azure Greece 2021

Maria-Anastasia Moustaka

During Didier his session you’ll discover how companies and partners that embrace AI will clearly create a competitive advantage and will grow at a faster pace than those who resist it. Future-orientated companies are already laying the foundations for this transformation, by conducting pilot projects and releasing AI applications for their daily operations. Of course, our technology evolves and we’re moving towards working with our partners and customers to create artificial intelligence that truly augments human capabilities.

AI as Driver of Transformation - Didier Ongena @CONNECT19

Codit

What's hot (20)

Integris software ppt

The iEx.ec Distributed Cloud: Latest Developments and Perspectives

EthCon Korea 28 May 2019

Cybersecurity

Research Topics in IOT

AI as a Catalyst for IoT

Why Cisco- for-Intelligence

Adopting Emerging Technologies

Cisco data analytics in ioe_rajiv niles_2015 nov

What is Cloud and what are the best practices?

Internet of things

Az-Internet of things

Fintech Belgium - MeetUp on The Right Tech for your FinTech - Philippe Cornet...

Sect f43

Iot & security automation-by Er. Nashet Ali

IoT: 3 keys to handling the oncoming barrage of use cases

Cryptolab Presentation: Crypto Searching Engine

The truth about IoT field gateways (Sam Vanhoutte @IoT Convention Europe 2017)

How I started with Azure IoT - Global Azure Greece 2021

AI as Driver of Transformation - Didier Ongena @CONNECT19

Viewers also liked

Cloud Foundry Summit 2015: Cloud Foundry and IoT Protocol Support

VMware Tanzu

bhide_connected_raleigh2016 (1)

sandhibhide

PDF_MEDECIN_EN

Dodow

De student-ondernemer

Prof. dr. Willy VAN EECKHOUTTE

Laboratorio 01

Alex Vt

ข่าวIt-9

ณัฐภัทร มีแก้ว

Ofimatica blogger

Frukencio

Diapositiva clase 30 minutos

Yoselina Hernandez

Árboles del bosque

Mònica Mira Bernàcer

Convocatoria pasantias Fondart 2016. Archivo Central Andrés Bello

ArchivoCAB2016

Resume_Buenrostro

Joana Erika Buenrostro

Shafeekh Kpp CV

school projects

Peter burke

Laboratorio 02 - FISICA I

Alex Vt

Viewers also liked (16)

Cloud Foundry Summit 2015: Cloud Foundry and IoT Protocol Support

bhide_connected_raleigh2016 (1)

PDF_MEDECIN_EN

De student-ondernemer

Laboratorio 01

ข่าวIt-9

Ofimatica blogger

Diapositiva clase 30 minutos

Árboles del bosque

Convocatoria pasantias Fondart 2016. Archivo Central Andrés Bello

Resume_Buenrostro

Shafeekh Kpp CV

school projects

Peter burke

Laboratorio 02 - FISICA I

Similar to Driving IT Transformation with Agile Analytics

Advanced Analytics: Going From Big Data to Big Answers

ajayc47

Date: 14th November 2018 Location: Keynote Theatre Time: 13:10 - 13:40 Speaker: Matt Aslett Organisation: 451 Research About: As 2018 draws to a close, Matt Aslett, Research VP, 451 Research looks ahead to 2019 and the key trends the research company’s Data, AI and Analytics team is anticipating for the year ahead, including the continued rise of DataOps; the increased importance of data science operationalisation; mainstream adoption of AI and machine learning; data platforms evolution; and the confluence of distributed database and blockchain technology in supporting the move towards planetary-scale data processing and analytics.

Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYOND

Matt Stubbs

Date: 13th November 2018 Location: Self-Service Analytics Theatre Time: 11:50 - 12:20 Speaker: Matt Pepper Organisation: MIcroStretegy About: In this session, Matt Pepper will demonstrate how MicroStrategy enables an Enterprise to provide: • Governed Data Discovery at scale • Freedom for departments to build applications whilst remaining compliant • The capability to link disparate data into a cohesive platform • The right information to the right person, in the right format, at the right time

Big Data LDN 2018: INTELLIGENCE EVERYWHERE – POWER TO THE PEOPLE

Matt Stubbs

Future-Proof Your Streaming Analytics Architecture- StreamAnalytix Webinar

Impetus Technologies

Madison Park Group actively tracks the broader Engineering, Manufacturing, and Supply Chain Software market and has dedicated significant attention to the Industrial IOT technology landscape. We are particularly interested in the rapid development of several trends: • Advancements in high-speed data ingestion and AI enabling highly accurate assessments of machine performance and reducing unnecessary downtimes • Low-code/No-code platforms and ready-to-use APIs simplifying software development processes and helping drive a wider range of IIoT uses cases and implementations • Integration of sensors into wearable devices and industrial assets in the manufacturing, healthcare and construction sectors, amongst others, creating real-time intelligence and novel asset tracking insights for operational efficiency and improved outcomes

MPG IIoT Primer - September 2022

Madison Park Group

NZS-4555 - IT Analytics Keynote - IT Analytics for the Enterprise

IBM z Systems Software - IT Service Management

Business Intelligence, Data Analytics, and AI

Johnny Jepp

Artificial intelligence capabilities overview yashowardhan sowale cwin18-india

Capgemini

Watch full webinar here: [https://buff.ly/2R4JjBX] Organizations today are data rich and insights poor. There is data everywhere. ERP systems, CRM systems, external data, data lakes and ponds. The real question to ask is “Are the users getting the insights they need when they need where they need to drive successful business outcomes”. Data Integration is a core pillar of the “Data to Value” journey. In this session you will hear how enterprises across industries are grappling with data, insights challenges and how organizations have adopted data virtualization to accelerate their "data to value" journeys. Watch this Denodo DataFest 2018 session to learn: How to reduce effort to get from data to value Hope to gain faster time to Insights How to reduce overall cost of ownership

Accelerating the Data to Value Journey

Denodo

Manufacturing, a slow-adopter of Analytics, is now catching up in leaps and bounds. Across all business domains, applying analytics is providing answers to the most critical questions of the business.With exponential expansion of data, data driven insights have become a strategic necessity. This booklet explores a few use cases of Big Data for manufacturing and how it can be leveraged. For more info visit: https://www.teamcomputers.com/businessanalytics/Manufacturing/Booklet-Manufacturing-Digital.pdf

Analytics in manufacturing

Saurav Kumar

Big Data, Big Thinking: Untapped Opportunities

SAP Technology

As enterprises strive to create a more data-driven culture, they want to put more data in the hands of more users across the organization. However, not all enterprise data is easy to access and understand, and most decision-makers lack the expertise to evaluate the quality of the data they’re using to know if it’s fit for purpose. To enable a culture of self-service analytics companies must get all of their data into one place where it can be accessed – like an enterprise data marketplace – and ensure its quality so it can be trusted by the data consumers. View this webinar on-demand to hear from Matt Aslett, Research VP, Data, AI and Analytics, 451 Research and Jennifer Cheplick, Senior Director, Syncsort about how a combination of technology and cultural change can enable enterprises to provide a foundation of data integration and data quality that arms your organization’s data consumers with the functionality to enable self-service analytics.

Enabling a Culture of Self-Service Analytics

Precisely

As the adoption of AI technologies increases and matures, the focus will shift from exploration to time to market, productivity and integration with existing workflows. Governing Enterprise data, scaling AI model development, selecting a complete, collaborative hybrid platform and tools for rapid solution deployments are key focus areas for growing data scientist teams tasked to respond to business challenges. This talk will cover the challenges and innovations for AI at scale for the Enterprise focusing on the modernization of data analytics, the AI ladder and AI life cycle and infrastructure architecture considerations. We will conclude by viewing the benefits and innovation of running your modern AI and Data Analytics applications such as SAS Viya and SAP HANA on IBM Power Systems and IBM Storage in hybrid cloud environments.

AI in the Enterprise at Scale

Ganesan Narayanasamy

Big Data Impacts on Hybrid Infrastructure and Management

Enterprise Management Associates

Get your data analytics strategy right!

SPAN Infotech (India) Pvt Ltd

Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions. To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter. This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to: - Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt - Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments - Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs - Enable real-time analytics with existing business intelligence and data assets.

Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from Forrester

Cubic Corporation

How To Pick The Best Analytics Tools: Product Analytics Landscape Here, we’ll talk about assessment criteria, key features, and greater for deciding on systems and gear that match your enterprise app development desires. Choosing the right solution for your data Because massive facts apply to the sort of huge spectrum of use app development instances, packages, and industries, it’s difficult to nail down a definitive listing of choice criteria. Types of data analytics tools & key features What is the gear used for massive facts analytics? Data analytics tools gear constitute a huge category, though they have a tendency to fall into some key groups. Customer data platforms Customer data platforms like customer relationship management platforms (CRM) seize purchaser facts that may be used to enhance strategies or promote products. However, CDPs take matters to the following level. Core capabilities: • 360-diploma view of the purchaser. • Connect more than one fact source. • Unifies purchaser facts throughout all linked structures. • Improve concentrated on for advertising campaigns. Business intelligence (BI) tools Today’s business intelligence (BI) assists companies to see iOS app development and apprehend facts. According to gartner, BI gear span 3 major categories. Online analytical processing, or OLAP, permits fact discovery, ad-hoc reporting, simulation fashions, overall performance control, and different complicated evaluation abilities. There’s additionally statistics transport–which serves up insights within the shape of visualizations, reports, and dashboards. And finally, BI integration–which offers metadata control and imparting app developers surroundings to assist your method. Core capabilities: • Data visualization. • Predictive modeling. • Data mining. • Forecasting. Customer analytics tools Customer analytics is designed to control the overall analytics technique from guidance to perception generation. In maximum instances, purchaser analytics systems include web development pre-built facts fashions for forecasting, propensity to buy, and numerous statistical evaluation strategies to apprehend purchaser conduct and optimize products, offerings, and reports. Core capabilities: • Granular segmentation. • Customer satisfaction Insights. • Statistical modeling. • Acquisition, retention, & churn metrics. Digital experience platforms Digital experience platforms is a new kind of enterprise-grade software development designed to optimize the purchaser revel in at each touchpoint. While DXPs overlap with purchasers revel in control systems, DXPs cognizance greater on streamlining strategies, coordinating and personalizing content material to customers throughout an extensive variety of channels which include the Internet of Things (IoT), virtual assistants, VR reports, and greater. Core capabilities: • API-first structure. • Multi-touchpoint control. • Dynamic templates for automating personalization. • Content control and transport.

How To Pick The Best Analytics Tool.pdf

Satawaretechnologies1

IT and marketing

Yudy Yunardy

Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.

ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...

DATAVERSITY

Four Key Considerations for your Big Data Analytics Strategy

Arcadia Data

Similar to Driving IT Transformation with Agile Analytics (20)

Advanced Analytics: Going From Big Data to Big Answers

Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYOND

Big Data LDN 2018: INTELLIGENCE EVERYWHERE – POWER TO THE PEOPLE

Future-Proof Your Streaming Analytics Architecture- StreamAnalytix Webinar

MPG IIoT Primer - September 2022

NZS-4555 - IT Analytics Keynote - IT Analytics for the Enterprise

Business Intelligence, Data Analytics, and AI

Artificial intelligence capabilities overview yashowardhan sowale cwin18-india

Accelerating the Data to Value Journey

Analytics in manufacturing

Big Data, Big Thinking: Untapped Opportunities

Enabling a Culture of Self-Service Analytics

AI in the Enterprise at Scale

Big Data Impacts on Hybrid Infrastructure and Management

Get your data analytics strategy right!

Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from Forrester

How To Pick The Best Analytics Tool.pdf

IT and marketing

ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...

Four Key Considerations for your Big Data Analytics Strategy

Recently uploaded

WSO2CON2024 - It's time to go Platformless

WSO2

WSO2Con2024 - WSO2's IAM Vision: Identity-Led Digital Transformation

WSO2

Evolving Data Governance for the Real-time Streaming and AI Era

confluent

WSO2Con2024 - From Blueprint to Brilliance: WSO2's Guide to API-First Enginee...

WSO2

WSO2Con2024 - Unleashing the Financial Potential of 13 Million People

WSO2

WSO2CON 2024 - OSU & WSO2: A Decade Journey in Integration & Innovation

WSO2

WSO2Con2024 - Organization Management: The Revolution in B2B CIAM

WSO2

WSO2CON 2024 - IoT Needs CIAM: The Importance of Centralized IAM in a Growing...

WSO2

ADR, or Architecture Decision Record, is a valuable tool in software development for several reasons. It provides a centralized location for documenting and tracking architectural decisions, aiding both current and future team members. ADRs enhance communication among team members by documenting the rationale behind architectural decisions, especially beneficial during onboarding of new team members or when revisiting decisions. They serve as a knowledge base, enabling teams to learn from past decisions and refine their decision-making process. Additionally, ADRs contribute to transparency by helping stakeholders understand the reasons behind specific architectural choices. As with any other tool or process, introducing them into an organization can face several obstacles, and overcoming these challenges is crucial for successful implementation. In this talk I go through some common problems and our way of solving them.

Architecture decision records - How not to get lost in the past

Papp Krisztián

WSO2CON 2024 - Unlocking the Identity: Embracing CIAM 2.0 for a Competitive A...

WSO2

WSO2CON 2024 - Building a Digital Government in Uganda

WSO2

WSO2Con204 - Hard Rock Presentation - Keynote

WSO2

This presentation covers the following topics: What is logging? The purpose of logging: Debugging The purpose of logging: Security The purpose of logging: Stats & analytics Traditional logging Traditional logging: Advantages Traditional logging: Disadvantages The solution: Large-scale logging Large-scale logging: Core principles Large-scale logging: Solution types Large-scale logging: Cloud vs on-prem Large-scale logging: Operational complexity Large-scale logging: Security Large-scale logging: Costs Large-scale logging: On-prem comparison - Elasticsearch - Grafana Loki - VictoriaLogs On-prem comparison: Setup and operation On-prem comparison: Costs On-prem comparison: Full-text search support On-prem comparison: How to efficiently query 100TB of logs? On-prem comparison: Integration with CLI tools VictoriaLogs for large-scale logging VictoriaLogs demo instance - Ingestion rate: 3600 messages / minute - The number of log messages: 1.1 billion - Uncompressed log messages’ size: 1.5TB - Compressed log messages’ size: 23GB - Compression ratio: 47x - Memory usage: 150MB VictoriaLogs CLI integration demo - Which errors have occurred in all the apps during the last hour? - How many errors have occurred during the last hour? - Which apps generated the most of errors during the last hour? - The number of per-minute errors for the last 10 minutes - Status codes for the last hour - Non-200 status codes for the last week - Top client IPs for the last 4 weeks with 404 and 500 response status codes - Per-month stats for the given IP across all the logs Large-scale logging solution MUST provide excellent CLI integration VictoriaLogs: (temporary) drawbacks VictoriaLogs: Recap - Easy to setup and operate - The lowest RAM usage and disk space usage (up to 30x less than Elasticsearch and Grafana Loki) - Fast full-text search - Excellent integration with traditional command-line tools for log analysis - Accepts logs from popular log shippers (Filebeat, Fluentbit, Logstash, Vector, Promtail, Grafana Agent) - Open source and free to use!

Large-scale Logging Made Easy: Meetup at Deutsche Bank 2024

VictoriaMetrics

WSO2CON 2024 - How to Run a Security Program

WSO2

WSO2Con2024 - GitOps in Action: Navigating Application Deployment in the Plat...

WSO2

WSO2CON 2024 - Not Just Microservices: Rightsize Your Services!

WSO2

WSO2Con2024 - Simplified Integration: Unveiling the Latest Features in WSO2 L...

WSO2

WSO2CON 2024 - WSO2's Digital Transformation Journey with Choreo: A Platforml...

WSO2

WSO2Con2024 - Enabling Transactional System's Exponential Growth With Simplicity

WSO2

WSO2CON 2024 - Building the API First Enterprise – Running an API Program, fr...

WSO2

Recently uploaded (20)