Global Manufacturing Analytics Market Insights Report 2018 – Sap Se, Alteryx, Inc., Zensar …

The primary aim of the global “Manufacturing Analytics” market research report is to evaluate, describe, and forecast the Manufacturing Analytics …

The primary aim of the global “Manufacturing Analytics” market research report is to evaluate, describe, and forecast the Manufacturing Analytics market globally based on the various factors like organization size, region, service, application, segments, deployment mode, and verticals. The global Manufacturing Analytics market research report distinctly evaluates every segment {Software, Professional Services, Managed Services}; {Predictive Maintenance & Asset Management, Inventory Management, Supply Chain Planning & Procurement, Energy Management, Emergency Management, Sales & Customer Management, Others} influencing the growth factors, restraining factors for the growth, contribution to the total Manufacturing Analytics market and the future developments.

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The global Manufacturing Analytics market research report consists of the following:

• The detail meaning of the Manufacturing Analytics market, which helps to evaluate and understand the market and its applications on a global level.

• The Manufacturing Analytics market is segmented into the detailed segments and has been evaluated thoroughly for better understanding and analysis of the market.

• To be in the competitive position, the global Manufacturing Analytics market research report provides full coverage of the factors contributing to the growth of the Manufacturing Analytics market, factors which are hampering the growth rate and the reason of such an activity is also evaluated briefly in the report so that Manufacturing Analytics market players can take decisions.

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The global Manufacturing Analytics market research report gives a comprehensive data and analysis about the worldwide Manufacturing Analytics market. The Manufacturing Analytics report further gives the data that one could rely on; which comes with in-depth analysis of Manufacturing Analytics market. Different factors like in-depth description of Manufacturing Analytics market, growth factors, segmentation, regional analysis, sales, supply, demand, manufacture analysis, recent trends, and competing companies are included in the Manufacturing Analytics report. The exquisite data provided in global Manufacturing Analytics market research report is explanatory in terms of quantity as well as quality.

Other Points Covered In The Global Manufacturing Analytics Market Research Report

• The global Manufacturing Analytics market research report also states the present opportunities in the Manufacturing Analytics market and future possibilities present in the market.

• All the necessary methods for collecting the data were used and required methodology as per the research was used to get to the results for the analysis.

• The global Manufacturing Analytics market research report consists of porter Five Forces model and SWOT analysis. For the validations of the data both Top-down method and Bottom-up method were used.

• All the major players Sap Se, Alteryx, Inc., Zensar Technologies Ltd., Statsoft, Inc., Computer Science Corporation(Csc), Sas Institute, Inc., 1010Data, Inc, Tibco Software, Inc., Oracle Corporation, Tableau Software leading in the Manufacturing Analytics market are mentioned in the report along with their regions-wise dominance.

• A detail region-wise segmentation is also been involved in the global Manufacturing Analytics market research report to make a clear.

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Big Data Analytics Market 2019 Estimated to Lock an Ineffaceable Growth | 12% CAGR Through …

Global Big Data Analytics Market, By Component (Software & Hardware), By Solution (Fraud Detection, Risk Management, Customer Analytics …

“Big Data Analytics Market”
Global Big Data Analytics Market, By Component (Software & Hardware), By Solution (Fraud Detection, Risk Management, Customer Analytics & Content Analytics) By End – User (Banking, Discrete manufacturing, Process Manufacturing, Government, telecom, Insurance, Transportation and Utilities)

Market Scope

The global big data analytics market is expected to expand at 12% CAGR from 2017 to 2023 to touch a size of USD 275 billion by 2023, states Market Research Future (MRFR). The preference of people shopping online owing to the availability of a slew of products on a common platform has led to large sets of data. Big data analytics has the capability to understand customer behavior according to the choices they have made and provide companies enough information for formulating strategies. Targeted advertising is one of the prime instances which have seen massive success thanks to the data.

The integration of internet of things (IoT) in homes and companies for thorough connectivity is possible thanks to big data analytics. Industrial automation for scaling their operations and operational efficiency is likely to augur well for the big data analytics market. Adoption of big data analytics by industrial sectors such as retail, telecommunications, and banking to gauge customer behavior can propel market growth till 2023.

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Segmentation Analysis

The big data analytics market report is segmented by component, solution, and end-user.

By component, it is segmented into hardware and software. The software segment is expected to generate significant revenue for the market till the end of the forecast period owing to the need for operational agility and performance in organizations. On the other hand, the hardware segment is likely to generate revenue at a modest growth rate owing to minimal changes in system architecture.

Solutions include customer analytics & content analytics, risk management, and fraud detection. Among these, the customer analytics & content analytics segment has the maximum revenue generating potential owing to the need for providing customized information for customers. Adoption of these software by the telecommunication industry for customer retention and loyalty purposes is likely to spur the segment growth till 2023. The risk management solution is likely to gain centerstage in light of various data breaches and scandals in financial institutions. The use of big data analytics by hedge fund managers to predict unforeseen events and take preventive measures is likely to drive the market demand over the forecast period.

Major end-users include transportation & utilities, discrete manufacturing, process manufacturing, government, telecom, banking, and insurance. Banking, discrete manufacturing, and process manufacturing can together account for nearly 50% of the revenue in the big data analytics market. This can be credited to the development of feed machine learning algorithms for foreseeing the possibility of malicious events. In addition, the potential of big data to portend

Competitive Scenario

Noteworthy names in the big data analytics market include Pentaho, VMware, Inc., Oracle Corporation, IBM Corporation, Datameer, Google Inc, Teradata Corporation, SAP SE, Microsoft Corporation, Hewlett Packard Enterprise, and Tableau Software. Growing digitization and adoption of virtualization has culminated in vendors offering innovative solutions for various industry verticals. In order to cope with the copious volume of data, players are establishing data centers to cater to high demand by BFSI, telecom, and manufacturing sectors.

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Regional Analysis

The North America region lead the big data analytics market owing to the United States and massive investments to foster development of the software. The uptick in number of mobile owners and widespread use of applications can drive the regional market growth. Automation is rapidly gaining speed with various industries switching to the technology to expedite their production rate. In addition, encouragement given to automated machine learning for performing repetitive tasks is likely to bode well for the market.

The Asia Pacific (APAC) region is expected to be lucrative for the big data analytics market owing to the demand by large corporations to sieve through data lakes and hubs for gauging consumer behavior. India and China are major regions likely to contribute to market demand owing to continuous developments in data science, advanced analytics, and predictive modelling. The shift to cloud is predicted to trigger the demand for big data analytics software immensely.

























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About Market Research Future:

At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services.

MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by Components, Application, Logistics and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions.

In order to stay updated with technology and work process of the industry, MRFR often plans & conducts meet with the industry experts and industrial visits for its research analyst members

Media Contact

Company Name: Market Research Future

Contact Person: Abhishek Sawant

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Big Data Analytics in Education Market Business Insights and Global Developments 2019 to 2025

This Report proposes compelling details of Big Data Analytics In Education market size, market share, contemporary trends, upcoming investment …

This press release was orginally distributed by SBWire


This Report proposes compelling details of Big Data Analytics In Education market size, market share, contemporary trends, upcoming investment opportunities, and other primary segments. The Big Data Analytics In Education analysis centers over numerous vital elements that influences global Big Data Analytics In Education industry along with the international economy. Historic overview, present market status, and futuristic projections of Big Data Analytics In Education industry are discussed in this study report.

The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market.

Top Companies in the Global Big Data Analytics In Education Market: – Abzooba, Analytic Edge, Fintellix Solutions Private, Heckyl Pvt, KloudData, Gramener, Germin8, LatentView, Indix, VIS Networks and Others.

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Behavior Detection

Skill Assessment

Course Recommendation

Student Attrition Rate Detection




Training & Development


For comprehensive understanding of market dynamics, the Global Big Data Analytics In Education Market is analyzed across key geographies namely: United States, China, Europe, Japan, South-east Asia, India and others. Each of these regions is analyzed on basis of market findings across major countries in these regions for a macro-level understanding of the market.

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Chapter 1: to describe Big Data Analytics In Education Introduction, product scope, market overview, market opportunities, market risk, market driving force;

Chapter 2: to analyze the top manufacturers of Big Data Analytics In Education, with sales, revenue, and price of Big Data Analytics In Education, in 2017 and 2018;

Chapter 3: to display the competitive situation among the top manufacturers, with sales, revenue and market share in 2017 and 2018;

Chapter 4: to show the global market by regions, with sales, revenue and market share of Big Data Analytics In Education, for each region, from 2014 to 2018;

Chapter 5, 6, 7, 8 and 9: to analyze the key regions, with sales, revenue and market share by key countries in these regions;

Chapter 10 and 11: to show the market by type and application, with sales market share and growth rate by type, application, from 2014 to 2018;

Chapter 12: Big Data Analytics In Education market forecast, by regions, type and application, with sales and revenue, from 2019 to 2025;

Chapter 13, 14 and 15: to describe Big Data Analytics In Education sales channel, distributors, traders, dealers, Research Findings and Conclusion, Appendix and Data source.

The report has 150 tables and figures browse the report description and TOC:


-Comprehensive assessment of all opportunities and risk in the Big Data Analytics In Education market.

-Big Data Analytics In Education market recent innovations and major events.

-Detailed study of business strategies for growth of the Big Data Analytics In Education market-leading players.

-Conclusive study about the growth plot of Big Data Analytics In Education market for forthcoming years.

-In-depth understanding of Big Data Analytics In Education market-particular drivers, constraints and major micro markets.

-Favourable impression inside vital technological and market latest trends striking the Big Data Analytics In Education market.

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MarketInsightsReports provides syndicated market research on industry verticals including Healthcare, Information and Communication Technology (ICT), Technology and Media, Chemicals, Materials, Energy, Heavy Industry, etc. MarketInsightsReports provides global and regional market intelligence coverage, a 360-degree market view which includes statistical forecasts, competitive landscape, detailed segmentation, key trends, and strategic recommendations.

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Crawl, walk, run and fly: The 4 stages of scaling website analytics

It can be intimidating to tackle the challenge of big data. While some tech-thinking companies have led the charge toward analytics, metrics and …

It can be intimidating to tackle the challenge of big data. While some tech-thinking companies have led the charge toward analytics, metrics and measurement, many companies are still grounded by the weight of having more questions than answers. How much data should I collect? What metrics are important to me? How do I get the best out of my investment?

If you’re ready to get up off the floor and dust off your data practices, it’s time to identify where you are and learn how companies mature to where they want to be. We will look at the four typical stages that companies go through when scaling website analytics.

Stage 1: Crawl

Every process must start somewhere – and this process should begin by asking the important questions about your organization. What are our effective key performance indicators (KPIs)? What are the driving factors that influence our business? What are the differentiators between our sectors of business that could influence our success?

Two factors to consider:

1. Important questions like those should be asked of all parts of your business. Marketing alone cannot answer these questions holistically without collaborating cross-departmentally. For example, marketing may surprise themselves with the insights and information that the shipping department or customer service team can offer for a better business understanding. A digital marketing team might think the company’s target demographic are young consumers, whereas in-store associates could tell them the reality is most shoppers are their parents. Website analytics sometimes don’t tell the whole story.

2. No answer is wrong! You must first set these benchmarks, as crazy as they may sound, to establish a philosophy that can be tested to see if it’s true. Consider yourself a researcher in your organization. Do you believe that time of year truly affects responses to marketing campaigns? Great – test these theories.

By establishing benchmarks, organizations can determine the proper way to collect the needed data to validate these guesses. To do so, find the largest white board available or create as many columns as you can in an Excel sheet – whatever your fancy – and bunker down until tough questions about your organization are answered.

Most importantly, this data should reflect aspects of your business that you can change or influence. In other words, working within your remit allows you to not only use the same process for each new test but also implement the results quicker and at scale.

Stage 2: Walk

You should now be able to determine which tools for your organization are needed – and subsequently which data points will be required – to test your theories. This can include general site metric collection such as Time Spent on Site or Bounce Rates or narrower figures like geographical distribution of high-value visitors.

Here are a few factors to keep in mind as you start this process:

  • Data collection tools are very good at giving you a lot of data, but many times it’s way more than you need. This results in companies attempting to collect as much as they can, getting overwhelmed with the results and entering in data paralysis. For example, Google Analytics can provide data about site trends, but it’s meaningless if the information is not tied to a business question.
  • The data analytics space is overly cluttered with many competing solutions with a sea of logos in Scott Brinker’s landscape, so do your due diligence to find the right tools to reflect your needs. The tool is just the start; implementing and training will lead to a larger investment of time and money than is typically planned and requires more team members than many companies account for.
  • Give yourself ample time to collect a rich data set before examining results to avoid anomalies or outside influences on your results such as the holiday season or a

    summer lull.

Stage 3: Run

Now comes the fun part – take that data and run with it. Create an organizational plan to make adjustments and changes based on your results to affect business. Did you find that your average cart size for sales goes up on the weekends? If so, then create marketing tactics to drive users on weekdays that include 2 for 1 or “Buy $100 and get $25 off” methods designed to increase total order size. Your next step will be to start a new experiment to see if these tactics worked to increase weekday sales. If they did, you now know the factors that control your business, and that is incredibly valuable to individual and organizational success.

Most importantly, now is the time when you can factor things out. Did you believe that your loyalty program was influencing return sales, but it turns out it did not? This could mean that your loyalty program needs to be overhauled, or that it cannot be the crux of marketing activities. It can be just as important to learn and confirm what is not working as what is.

Stage 4: Fly

It’s time to soar. Many marketers view their website in a bubble. The truth is that a website is just one channel that users will interact with when engaging with your brand. And not every user is made the same – some will use it for research and buy in store in commerce scenarios while certain groups will use it primarily before speaking with a sales person in other industries. Now that you can properly track and map your website using the tools and methods you have found, it’s time to expand that thinking to other touch points. Are you mapping users from your website to in-store conversion? Do your local event sponsorships lead to users joining your mailing list? Do users who have a positive experience on your support channels typically become better brand advocates on their social media channels? What method can you use to link these sales?

It can be a daunting task to connect all the dots in a sales funnel from the start, so find those easy wins by beginning with your e-commerce or dot com channel and use those powerful data tools to learn what you need before moving to the next channel. For in-store or call orders, for example, customers can be incentivized to use their online session ID to make for easier cross-channel analysis.

Are you ready for the challenge?

The technology space for web analytics tools has skyrocketed over the last few years. Buzz words like “Customer Journey Analysis” and “Machine Analytics” create intimidating spaces that marketing teams are entering into with caution flags waving. Being a member in this space myself, companies that come in with a purpose and goal before considering tactics or tools succeed far more often than those just looking for the quick fix to satisfy the C-suite.

You won’t become an expert in a day. You might idolize those companies out there like Amazon and Google who seem to know about you before you know yourself. While they might be models of data collection and analytics, they took years to get there – their own Crawl, Walk, Run and Fly process that included many of the baby steps you might be getting ready to take. Enjoy the process, take your time and you will achieve your desired level of success, one answer at a time. Keep flying, so platforms and processes provide the complete view of business success you need to compete online and off.

Opinions expressed in this article are those of the guest author and not necessarily Marketing Land. Staff authors are listed here.

About The Author

Jeff Cheal is the Director of Product Strategy for Personalization, Campaign and Analytics at Episerver. He has an extensive background in advertising sales, software and marketing strategy. He is based out of New York, serving the North American market as an ambassador for the Episerver product suite, staying connected with both the partner network and customer base.

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Stay Ahead of the Growing Security Analytics Market With These Best Practices

Enter security analytics, which mixes threat intelligence with big data capabilities to help detect, analyze and mitigate targeted attacks and persistent …

As breach rates climb and threat actors continue to evolve their techniques, many IT security teams are turning to new tools in the fight against corporate cybercrime. The proliferation of internet of things (IoT) devices, network services and other technologies in the enterprise has expanded the attack surface every year and will continue to do so. This evolving landscape is prompting organizations to seek out new ways of defending critical assets and gathering threat intelligence.

The Security Analytics Market Is Poised for Massive Growth

Enter security analytics, which mixes threat intelligence with big data capabilities to help detect, analyze and mitigate targeted attacks and persistent threats from outside actors as well as those already inside corporate walls.

“It’s no longer enough to protect against outside attacks with perimeter-based cybersecurity solutions,” said Hani Mustafa, CEO and co-founder of Jazz Networks. “Cybersecurity tools that blend user behavior analytics (UBA), machine learning and data visibility will help security professionals contextualize data and demystify human behavior, allowing them to predict, prevent and protect against insider threats.”

Security analytics can also provide information about attempted breaches from outside sources. Analytics tools work together with existing network defenses and strategies and offer a deeper view into suspicious activity, which could be missed or overlooked for long periods due to the massive amount of superfluous data collected each day.

Indeed, more security teams are seeing the value of analytics as the market appears poised for massive growth. According to Global Market Insights, the security analytics market was valued at more than $2 billion in 2015, and it is estimated to grow by more than 26 percent over the coming years — exceeding $8 billion by 2023. ABI Research put that figure even higher, estimating that the need for these tools will drive the security analytics market toward a revenue of $12 billion by 2024.

Why Are Security Managers Turning to Analytics?

For most security managers, investment in analytics tools represents a way to fill the need for more real-time, actionable information that plays a role in a layered, robust security strategy. Filtering out important information from the massive amounts of data that enterprises deal with daily is a primary goal for many leaders. Businesses are using these tools for many use cases, including analyzing user behavior, examining network traffic, detecting insider threats, uncovering lost data, and reviewing user roles and permissions.

“There has been a shift in cybersecurity analytics tooling over the past several years,” said Ray McKenzie, founder and managing director of Red Beach Advisors. “Companies initially were fine with weekly or biweekly security log analytics and threat identification. This has morphed to real-time analytics and tooling to support vulnerability awareness.”

Another reason for analytics is to gain better insight into the areas that are most at risk within an IT environment. But in efforts to cull important information from a wide variety of potential threats, these tools also present challenges to the teams using them.

“The technology can also cause alert fatigue,” said Simon Whitburn, global senior vice president, cybersecurity services at Nominet. “Effective analytics tools should have the ability to reduce false positives while analyzing data in real-time to pinpoint and eradicate malicious activity quickly. At the end of the day, the key is having access to actionable threat intelligence.”

Personalization Is Paramount

Obtaining actionable threat intelligence means configuring these tools with your unique business needs in mind.

“There is no ‘plug and play’ solution in the security analytics space,” said Liviu Arsene, senior cybersecurity analyst at Bitdefender. “Instead, the best way forward for organizations is to identify and deploy the analytics tools that best fits an organization’s needs.”

When evaluating security analytics tools, consider the company’s size and the complexity of the challenges the business hopes to address. Organizations that use analytics may need to include features such as deployment models, scope and depth of analysis, forensics, and monitoring, reporting and visualization. Others may have simpler needs with minimal overhead and a smaller focus on forensics and advanced persistent threats (APTs).

“While there is no single analytics tool that works for all organizations, it’s important for organizations to fully understand the features they need for their infrastructure,” said Arsene.

Best Practices for Researching and Deploying Analytics Solutions

Once you have established your organization’s needs and goals for investing in security analytics, there are other important considerations to keep in mind.

Emphasize Employee Training

Chief information security officers (CISOs) and security managers must ensure that their staffs are prepared to use the tools at the outset of deployment. Training employees on how to make sense of information among the noise of alerts is critical.

“Staff need to be trained to understand the results being generated, what is important, what is not and how to respond,” said Steve Tcherchian, CISO at XYPRO Technology Corporation.

Look for Tools That Can Change With the Threat Landscape

Security experts know that criminals are always one step ahead of technology and tools and that the threat landscape is always evolving. It’s essential to invest in tools that can handle relevant data needs now, but also down the line in several years. In other words, the solutions must evolve alongside the techniques and methodologies of threat actors.

“If the security tools an organization uses remain stagnant in their programming and update schedule, more vulnerabilities will be exposed through other approaches,” said Victor Congionti of Proven Data.

Understand That Analytics Is Only a Supplement to Your Team

Analytics tools are by no means a replacement for your security staff. Having analysts who can understand and interpret data is necessary to get the most out of these solutions.

Be Mindful of the Limitations of Security Analytics

Armed with security analytics tools, organizations can benefit from big data capabilities to analyze data and enhance detection with proactive alerts about potential malicious activity. However, analytics tools have their limitations, and enterprises that invest must evaluate and deploy these tools with their unique business needs in mind. The data obtained from analytics requires context, and trained staff need to understand how to make sense of important alerts among the noise.

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