If your data strategy isn’t successful in fetching you leads, profits, or successful deals, you are surely on the wrong track. Here are some checkpoints to help you identify the issues.
Is your project management office using spreadsheets to manage your project lifecycles? Here are 10 reasons you should be ditching spreadsheets for a purpose built project portfolio management solution.
Take a look at this interesting presentation on ➡ 3 Pillars to become successful with your analytics strategy
Inculcate a culture of analytics, have the right people on-board, get your organization strategy on one page, and have the right architecture and data management strategies in place.
Link: https://bit.ly/2BanJcW
Data Analytics with Managerial Applications InternshipJahanvi Khedwal
Data Analytics with Managerial Applications Internship under Prof. Sameer Mathur-Making Advanced Analytics Work for You by Dominic Barton and David Court-presentation
Is your project management office using spreadsheets to manage your project lifecycles? Here are 10 reasons you should be ditching spreadsheets for a purpose built project portfolio management solution.
Take a look at this interesting presentation on ➡ 3 Pillars to become successful with your analytics strategy
Inculcate a culture of analytics, have the right people on-board, get your organization strategy on one page, and have the right architecture and data management strategies in place.
Link: https://bit.ly/2BanJcW
Data Analytics with Managerial Applications InternshipJahanvi Khedwal
Data Analytics with Managerial Applications Internship under Prof. Sameer Mathur-Making Advanced Analytics Work for You by Dominic Barton and David Court-presentation
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: "use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems".
How data scientists add value to your business organizationJanBask Training
Mostly data scientists are being trained in computer science, math and statistics. The expertise of data scientists can be used in data visualization, data mining, and the information management.
https://www.janbasktraining.com/data-science
The Three Pitfalls of Business Expansion – and how you can avoid themMadeline ten Krooden
Is your business information helping or hindering you? Our latest masterclass series shows you how to avoid the pitfalls.Spot the three pitfalls of business expansion and learn how to avoid them. Our new masterclass series has the details.
Thinking through what implications the patterns hold for their businesses, companies can find ways to engage more fully with the digital economy—and cash in on its promise.
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
How the analytics industry has been affected by descriptive, predictive and prescriptive techniques and how these traditional analytical techniques are going to transform the industry in future
Generating Business Value thro’ Integrating Data Analysis into planning and...NareshChawla
Data analysis is the lifeline of any business. No business can survive without analyzing available data. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy or compute process capability or predicate future trends or breakdown a big issue into smaller but manageable issues; data analysis is the key to all the problems.
This 12-page brochure describes Mountain Stream Group's Nexus Control Loop(TM) 6-step design process. The process closes the loop on your success by making it a performance standard and is programmed to your application.
View this presentation to find out how clean data can help your business and an introduction to QGate's Paribus Discovery and Paribus Interactive products that solve duplicate data problems.
The data management procedure employed by your firm is capable of building your brand or breaking it all over. So, be wise in choosing the right strategy.
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: "use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems".
How data scientists add value to your business organizationJanBask Training
Mostly data scientists are being trained in computer science, math and statistics. The expertise of data scientists can be used in data visualization, data mining, and the information management.
https://www.janbasktraining.com/data-science
The Three Pitfalls of Business Expansion – and how you can avoid themMadeline ten Krooden
Is your business information helping or hindering you? Our latest masterclass series shows you how to avoid the pitfalls.Spot the three pitfalls of business expansion and learn how to avoid them. Our new masterclass series has the details.
Thinking through what implications the patterns hold for their businesses, companies can find ways to engage more fully with the digital economy—and cash in on its promise.
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
How the analytics industry has been affected by descriptive, predictive and prescriptive techniques and how these traditional analytical techniques are going to transform the industry in future
Generating Business Value thro’ Integrating Data Analysis into planning and...NareshChawla
Data analysis is the lifeline of any business. No business can survive without analyzing available data. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy or compute process capability or predicate future trends or breakdown a big issue into smaller but manageable issues; data analysis is the key to all the problems.
This 12-page brochure describes Mountain Stream Group's Nexus Control Loop(TM) 6-step design process. The process closes the loop on your success by making it a performance standard and is programmed to your application.
View this presentation to find out how clean data can help your business and an introduction to QGate's Paribus Discovery and Paribus Interactive products that solve duplicate data problems.
The data management procedure employed by your firm is capable of building your brand or breaking it all over. So, be wise in choosing the right strategy.
Importance of building a data strategy for business growthKavika Roy
https://www.datatobiz.com/blog/data-strategy-for-business-growth/
We all know that an immense amount of data is generated with every passing second. From our Uber ride to ordering a burger in McDonald’s or every transaction that we make at the ATM, everything is recorded and stockpiled for further analysis.
In the past, data was perceived as nothing but a by-product of business activity, but today it has a value and is considered more as an economic asset.
All the big enterprises generate numerous data, which they want to utilize for the benefit of their company but still struggle in managing, sharing, and turning it into useful information. If you are amongst one of those business owners who are looking forward to utilizing the data that has been just stored in your systems, you have come to the right place.
Getting Ahead Of The Game: Proactive Data GovernanceHarley Capewell
Data today is getting bigger, more widely available and
changing more quickly than ever before. Data Governance
coach Nicola Askham shares her advice on why you
need to embrace Data Governance NOW and what good
governance looks like.
Many of today’s business challenges can reveal a number of weaknesses throughout your back-office. You need only be aware of the signs. Increased market and competitive forces are driving more and more business executives to evaluate their support functions such as procurement, finance, human resources and information technology. Service level agreements, complex billing requirements, poor data management and dispirit systems throughout these functions can bleed cash and quickly demotivate your workforce.
Challenges Of A Junior Data Scientist_ Best Tips To Help You Along The Way.pdfvenkatakeerthi3
One of the most fascinating fields today that is enabling businesses to improve their operations is data science.
Databases, network servers and official social media pages.
Data analysts and data scientists are becoming commonplace in most businesses nowadays and employing them on a full-time basis creates a severe financial burden to the management; this is where HLB HAMT and their data analysis professionals step in.
Most of the businesses are sitting on various types of data, which they are assessing during their business operations. But most of the time, the available data is not effectively organized or consolidated to analyze and interpret.
This whitepaper aims to assist Chief Data Officers in promoting a data-driven culture at their
organization, helping them lead the enterprise on a digital transformation journey backed by
analytical insights.
Data discovery, channeling data, data visualization, and problem-solving; our experts are ready to help any businesses who need assistance on big data.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
Similar to Checklist To See If Your Current Data Strategy Is Outdated (20)
Big Data’s Potential for the Real Estate Industry: 2021PromptCloud
Many real estate firms have long made decisions based on a combination of intuition and traditional, retrospective data. Today, a host of new variables make it possible to paint more vivid pictures of a location’s future risks and opportunities.
In this quickly technologizing industry, arming your team with the most robust data available and making important decisions based on the data is going to determine who wins and loses.Big data will become the key basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy. In this white paper, we explore the real estate outlook for financial investment in 2021 and use cases demonstrating the power of data in transforming the real estate industry.
Looking for a similar tool like Octoparse? We have conducted thorough research on tools that can process web data to draw actionable insights. The results were amazing, as most of the web scraping tools that are available in the market offer unique value propositions for unique data requirements, differing from business to business. As you read further, you will be able to figure out the best Octoparse competitors & alternatives for your organizational data needs.
Most of the users use Octoparse to figure out how the market is functioning and to conduct data verification. However, conducting broad-level research might not always work for companies running in a niche domain. There are a lot of tools available today, offering value services like: easy usage, value for money, better user rating, getting structured data and etc, that could be a great fit for your business requirements. But first, let’s understand how Octoparse web scraping works.
How to Choose the Right Competitors & Alternatives of ParseHub Web Scraping Software?
Web scraping is generally used to understand the marketplaces and get visibility on the pricing structure of your competitors in the niche your company is invested in. Getting a fair understanding of various web scraping products and Parsehub competitors and alternatives will enable you to make informed decisions to grow your business. Read more to know how these tools work, scaling, delivery, target customers, and shortcomings. Read further, to take a look at companies offering data services according to industries, user rating, accessibility, deliverables, speed, interface, customer service, and technical challenges. But before we dive into this, let’s understand what web scraping is and how to access the ParseHub Web Scraping Software.
Product Visibility- What Is Seen First, Will ppt.pptxPromptCloud
Putting your products on multiple eCommerce websites may give you a broad reach, but might not be enough for them to be “visible”. Creating quality blogs or short videos on several themes could help you find a wider reach!You can partake in multiple activities like –
Talk about the USP of your products or highlight the star products.
Share a comparison of your products with your competitors.
Discuss topics related to the your product and services delivered by you. When users go to a product page, right after the images, they look at the heading and the description. Let’s take an example of a product listed on Amazon, to figure out how both headings and descriptions can increase the sales of your products.Read the complaints they have with similar products. Decide upon the size and quantity options that would suit the user base most. Understand the price point that is desired. And lo and behold you would have increased your product visibility!
Data plays a vital role in the fashion industry. It is used to drive decisions and strategy that generate sales, gain a better understanding of customers, and boost overall profit. Fashion designers and companies use data on a daily basis run a successful fashion business. However, the commonly perceived data used by fashion designers differ from the standard mathematical statistics commonly associated with the term “data”. Hence, data is not usually associated with the word fashion.
But, today’s top fashion houses are deploying several ways to use emerging analytical technologies in fashion retail today. We explore how the modern fashion industry uses data.
Data Standardization with Web Data Integration PromptCloud
Before analyzing data aggregated from multiple sources, it is essential to first standardize the datasets. At PromptCloud, we put special emphasis on this process and understand that as a web crawling company, our solution must enable our clients to integrate data efficiently.
Zipcode based price benchmarking for retailersPromptCloud
Here's our case study of a popular e-commerce platform based out of the United States, seeking data to be extracted from the web to enhance its pricing and product strategy.
Analyzing Positiveness in 160+ Holiday SongsPromptCloud
It is known that during any kind of celebration music is indispensable and the holiday season is no different. Since this time of the year brings positiveness, we decided to analyze the holiday songs to uncover some interesting insights related to musical features and positiveness in songs.
What a year 2018 has been for the data ecosystem! We believe the high-magnitude and rapid demand for alt-data (especially web data) from companies of various sizes across industries is a remarkable element of this year.
For PromptCloud, it has always been about moving the needle when it comes to democratization of web data access. We’re fortunate enough to have built a team that absolutely loves the ease of information flow offered by the internet and wants to share the same with the businesses across the globe.
We’re on a journey to make a dent in the alt-data space with laser-focused teams that are paranoid about the data quality delivered to our customers. In honor of our successful clients and their incredible growth powered by our talented data wizards, let’s spare a moment to celebrate PromptCloud’s year in review.
10 Mobile App Ideas that can be Fueled by Web ScrapingPromptCloud
We discuss various applications of web crawling and alternate data to fuel 10 potential mobile apps. The ideas range from reverse image search engine powered AI to voice of customer in ecommerce domain.
How Web Scraping Can Help Affiliate MarketersPromptCloud
This presentation discusses how web scraping services can be deployed to acquire trending ecommerce product data for better conversion in affiliate marketing.
In this study, we analyze the reviews for the top 10 most expensive and least expensive hotels based out of London to compare various aspects of the rating and review text.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
The affect of service quality and online reviews on customer loyalty in the E...
Checklist To See If Your Current Data Strategy Is Outdated
1.
2. Can you vouch for your Big Data strategy? Is it in
place and adept at current operational needs?
3. If your data strategy isn’t successful in fetching
you leads, profits, or successful deals, you are
surely on the wrong track.
4.
5. Here’s a quick glimpse of the common data
strategy errors…
6. Unless you are aware of organizational needs or have a profound
idea of business targets, data collection won’t fetch any results.
Identifying accurate data points amidst vast data sets is almost
impossible.
7. Collecting huge volumes of data can lead to the accumulation of
unused and unutilized data sets. That further creates opportunities
for ‘dark data.’ Effective and proper storage becomes difficult, and
that might lead to data wastage too.
8. Collecting irrelevant data sets is no less than a serious offence. You
will not only miss out on the right business opportunities, but also
make misinformed moves, faulty decisions, and wrong
assumptions.
9. Controlling and governing data sets happen to be crucial requisites.
When you lose control over data, seamless incorporation and
implementation of these data sets become impossible.
10. Visualizing your data is crucial, as that gives you an idea of its
benefits. Improper visualization can lead to inaccurate and
imperfect implementation. As a consequence, the organization will
fail to reach the desired goals.
11.
12. Here’s a checklist to help you identify the
holes in your data strategy…
13. If you lack a well established data center, your chances of gaining
access to updated data sets reduce to a great extent.
14. Make sure your data strategy is built with processes, operations,
and business functions in mind. The entire affair should be scalable
where your data strategies will grow along with the enterprise.
15. If you wish to stay ahead of the growth curve, embracing speed,
dexterity and agility will be crucial.
16. If you fail to govern organizational data, it will become difficult to
comprehend the current necessities. Mastering data governance is
essential to maintaining a healthy data strategy.
17. You have to strategize hardening for your databases, middleware,
applications, tools, etc. – to address the full scope of SLAs
associated with the main use cases.
18. If you can’t supply, add, or reallocate new storage, evaluate and
network capacity on the big-data platform in a quick, cost-
effective, modular way to meet new requirements, the platform is
not ready for production.
19. Make sure you build, update and change your
data strategy at regular intervals, as that’s the key
to reaping the maximum benefits from big data.