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Data

The Challenges Facing Location Data & Location Intelligence In 2020

What is location data and location intelligence

In 2019 the number of connected devices will continue to grow to its highest ever. With more devices and increased sensors, the amount of data generated will explode.

It will be more accessible than ever before to use data to inform everything from business intelligence to advertising. Location-based data will be more accurate than ever before. These factors will mean it be used more commonly in areas where big data can have a profound effect.

Across a wide range of industries location data and location intelligence is helping to maintain a competitive edge. It is being used to deliver insights that have previously been inaccessible.

Location intelligence is the practice of using location data to achieve business outcomes. The process uses mobile devices and sensors to visualise and enrich understanding of how devices move in the real world.

The growing amount of precise data available will provide some challenges for those in the industry.

Privacy concerns will remain front and centre as they have done for most of 2018. Data quality is still an issue that many providers need to address. Businesses will need to find an effective and seamless method of consuming and getting the most value from location data.

Here’s what we think will be the biggest challenges facing the location data and location intelligence industry.

 

Challenges in location data

With this in mind, what are the biggest challenges that location faces in 2019?

 

Consent and privacy concerns

2018 saw the introduction of GDPR in Europe.  In the US the upcoming CCPA act data privacy will still be front and centre in the data community. We are quickly moving towards a world where each individual will have control over their data.

Businesses using location data will need to take a similar approach. It’s pivotal to allow the individual to take control of their data. Companies must inform users of how their data is used. They must provide clear opt-in and opt-out solutions so that transparency can be placed at the centre of the big data revolution.

Businesses that utilise location data will need to be clear on how they collect and use consumer data. Location data providers need to have a clear opt-in process that allows consumers to understand how their data is used.

Data providers should provide solutions at the point of collection which allow them to manage consent preferences all the way through to the point of data use.

 

Data quality and standardisation

Many businesses look at a lack of accuracy in the location data that fuels location intelligence as a big challenge for the industry.

With the growth of geodata, many new providers have offered sub-par datasets with limited accuracy. These providers often have little transparency in how their data is collected and how accurate it is. For the proper application of location data, businesses need to be able to verify the data collection methodology.

The most accurate providers will be able to verify their first-party data sets. They can provide a detailed explanation around data collection. Accuracy in location data can be useless when it is just a metre out.

To avoid these poor data sets, location intelligence solutions should actively verify and remove inaccuracies in the data. The space requires a clear and transparent process for data users to see the entirety of the process, from collection to use.

For example, Tamoco is providing an extra data set which provides a clear and transparent rating for every data point collected. Our visits dataset demonstrated the accuracy of each datapoint. It can be used by business to filter out inaccuracies. It also provides transparency, allowing the end data user to understand data collection and data methodology.

 

Being ready to consume the data

More industries are looking to benefit from location intelligence. It will be more critical than ever for these businesses to be ready to consume the dataset.

For some, the use of location data to understand movement patterns will be a new data source. Providing a dataset that is ready for instant consumption will be a crucial challenge for many location intelligence providers.

Another challenge will be creating a solution that allows business to combine and manipulate location data alongside current datasets. This will maximise the effect that location intelligence can have on business functions.

There will be a move towards integrated solutions that will work as a service for location intelligence. With standardisation, it will become easier for companies to ingest large amounts of location data.

 

Effectively cleaning and normalising the data.

Many businesses that are interested in location data have concerns when processing data. Location data can be a challenge to clean and normalise for a business’ analytics or other functions.

These challenges usually involve transforming the data into a workable format. Verifying the data is up to date, and accurate is another issue for companies using location data.

A related but slightly different challenge is being able to understand when the data is appropriate for specific analytics.

At Tamoco we are working closely with our partners to create a data source that is thoroughly verified and cleaned. Our sensor driven approach makes us industry leading concerning accuracy and provides a more precise base to clean our data for customer use.

In 2019 location data providers will need to work closely with their customers to understand the data cleansing process. They must provide standardised documentation and solutions that help partners to get the most from the data.

The potential for location data remains enormous. In 2019 challenges in data collection and processing will need to be addressed. Fine-tuning a robust process that addresses security concerns will be the highest priority. Developing and managing the standardisation of location data will be another.

Categories
Data

Location Data And Location Intelligence In 2021 – What To Expect

What is location data and location intelligence

In 2019 the number of connected devices will produce more data than ever before. As this increases the data will become fundamental to many industries and businesses.

Data will fuel everything from city planning to advertising and marketing. Location-based data will be more accurate than ever before, and it will be used more in areas where big data has already had an initial impact.

Across many industries, location data and location intelligence is proving to be a powerful tool for companies looking to maintain a competitive edge. It is being used to deliver insights that have previously been inaccessible. In 2019 accurate and precise location data will be leveraged to generate new insights and power better understandings of behaviour and movement.

Location intelligence is the practice of using location data to achieve business outcomes. This uses mobile devices and sensors to visualise and enrich understanding of how devices move in the real world.

These interactive data sets are used alongside a business’ current solutions to create a powerful competitive edge and optimise business functions.

With strong roots in advertising location data and location intelligence are increasingly being utilised in new verticals from finance to planning and construction. In 2019 location data will be more commonplace, and location intelligence solutions will be fundamental to the success of many different businesses.

 

The future of location intelligence in 2019

With the rise of location data and location intelligence businesses will see new use cases and more powerful datasets.

Changes that we expect to see in the space will include the following:

 

Combining datasets

The next step for location data sets is combining with extra information to enhance the value for data users.

In 2019 data providers will provide more detail around datasets as standard. Demographics and other metadata will add value out of the box. As well as this there will be an increased number of businesses that will combine their datasets with identifiers in the location data to improve functionality and create new ways of understanding existing datasets.

This also means that it should be clear and transparent which data sets are used. Providers should have a standardised way that business can filter and understand which data points should be ingested and used alongside the correct datasets.

In 2019 location data will be more transparent and more accessible to use alongside existing customer datasets to maximise business functions. By linking location data businesses will instantly have a more detailed view of their customers or relevant segments.

 

More uses

Location intelligence is beginning to gain prevalence outside of the marketing industry.

A considerable majority of marketers (82%) are now planning on upscaling their use of location data over the next two years.

As location data use in marketing reaches a critical point, we will begin to see it adopted more readily in other industries and feature in new use cases.

As more organisations document and formalise their use of location intelligence the value of these datasets will become more apparent and are adopted outside of the traditional verticals, such as marketing and advertising.

While marketing and advertising are still the most common use case for location data and location intelligence; there is a dramatic increase in both the number of industries that say they will invest more in the technology and those that already have.

Expect to see location data involved as a fundamental part of any effective BI strategy. Understanding device movement with precision will fuel predictive capabilities. Location intelligence will be widespread in everything from City planning through to logistics, automation and investment.

New use cases will emerge. Location data will be used to understand global trends for journalistic purposes to understanding environmental changes and populations.

 

Data accuracy and quality

New industries will require better accuracy and a better way of consuming the insights that location data can provide.

In 2019 we will move away from talking about postcodes and large scale geofencing. Instead expect to see granularity, three-dimensional location and precise location intelligent solutions.

Businesses must take advantage of a focus on accuracy in the industry and start visualising and analysing datasets at a deeper geographic level.

Many businesses are currently using geographic boundaries such as postcodes or large geofences around more extensive areas.

The technology is now much more granular than this and businesses should be aware of the new and custom functionalities that the leading location data solutions can provide.

Expect to see more detailed datasets that include variables to filter out inaccuracies and other data points that are not useful for the end data user. These processes will become automatic in 2019, and the best providers will be able to boast systems that can automatically detect these outliers in the data.

 

Analysing the data

As big data becomes fundamental to many organisations, more datasets will be available.

More data types mean better unification is needed for customers because of this 2019 will see the emergence of LaaS (Location as a service).

Ready to use location platforms will empower businesses to leverage the unique insights that location data offers. It will allow them to visualise and digest insights easily. It will support manipulation of data and provide functionality to integrate these into current business functions and solutions.

These platforms will be closer to real-time than before and provide more granular insights that will allow businesses to act immediately on these insights.

The experts in precise location

Get in touch to get ahead with location intelligence or to see how you can use location data to benefit your business.

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Categories
Business Data

5 Amazing Ways Big Data is Transforming the Education Sector 

Big data and Education are closely interconnected as it helps school, colleges, universities, institutions and many more educational organizations to make the overall decision about in the organization’s overall outpace, scholastic outreach, and much more. 

Big data analytics in education will not only help in academic performance but also increases the efficiency and effectiveness of the faculty as well as technology. 

The educational Sector these days prefer big data in education as it makes sure to reduce business expenditure which will eventually be beneficial for the organization. 

Not only the present time, but data for education will enable you to predict different trends that will be adopted in the future in the respective industries. It leads the employees to have better planning which will help in the overall development of the education sector. 

Image Source: IntechOpen 

As rightfully said by Chris Lynch, an American Writer of Books “Big data is at the foundation of all the megatrends that are happening.” So, your educational institution and students will for sure benefit from big data. 

Importance of Learning About Big Data

Big Data helps all learners, students, professors, teachers and individuals involved in the educational sector to understand the overall strategies as well as the individualized learning process.  

Image Source: Springer Open 

Let’s get familiar with the importance of studying/researching big data in the education sector: 

  • Big data helps to map student learning by measuring the teaching-learning process of the classroom. 
  • According to Salt Lake Tribune data for education not only helps teachers and students but is also equally significant for financial and administrative management. 
  • In general, the cost-saving process will be quick, simple, efficient and easy to adapt with not much confusion. 
  • You can do individual manual searches or studies based on the initial search as per your own preferences and requirements. 
  • Along with big data and affordable writing services, you can increase accessibility and save costs. 

The list simply goes on and on so we have concluded the importance of learning about education data analysis in the best five points. 

Ways Big Data is Transforming the Education Sector

Even today many people think and assume that big data is significant when it comes to only business. But this is not a precise piece of information. 

Not only in business but big data is important for the financial market, detection of fraud, newly adapted smart traffic system, the healthcare industry, the government sector, media and much more. Along with all these sectors the Education sector is one of the most important sectors. 

As we already know about the importance of big data, let’s get familiar with all the ways big data is transforming the education sector. 

Find Out Strengths of Students 

Learning about big data doesn’t only solve short-term problems rather it focuses more on long-term things. It will help students to analyze, influence, discover and ascertain long-term goals. This will eventually help them out in the future. 

Big data can be helpful for students and teachers as it will help them gain better information about all the possibilities that are likely to appear in the upcoming days. This way they will get better to sort of thing and tackle all of the hassles that come through their path. 

Not only about the overall prospects but big data will also help them have a better understanding of themselves. 

Improve the Grading 

When an educational institution decides to let big data foreplay in their institution, they will be able to gain information about all the tracks and records of the students. 

This way the teachers will be able to gather all the fields that interest students through which creativity and collaboration will increase in the learning process. Students can gain what they want and teachers can get the proper feedback through which they can help students improve. 

Not only this but it has a long positive impact as this way they can gain all the necessary skills which will eventually help them in their career path. Hence, this way big data will help to transform the overall education sector. 

Targeted International Recruiting 

The application process is considered one of the most important factors in the education sector. More the number, the better as when more students enroll for better education more amazing students will gain quality education. 

This education will eventually help them to gain better jobs which will eventually improve their lifestyle and increase the overall economy of a nation. 

The application process can be made better using big data analysis in education by analyzing and guessing all the possible and essential factors. When analyzed better things can also be planned in a better way. 

Minimizes the Dropout Rate 

As everyone will get what they need, especially the students will be satisfied. This will eventually decrease the dropout rate of students from schools, colleges and universities. 

Sometimes even bad results discourage students, but that’s not the case once the education sector starts using big data. It is said that the analysis made with the help of big data will help both teachers and students understand problems and find out solutions without any hassle. 

There is less rate of error found after using the big data, not only that it will eventually help students to improve their overall academic performance. Hence it will improve their rank and performance which will eventually result in a deduction of the dropout rate. 

The Efficiency of Technology in Education 

In the 21st era, technology plays an important role as it provides opportunities for people to change their overall life. One without technology information can actually be a brick on the wall. Due to the use of big data in education, all the individuals involved in this sector will gain basic knowledge about it. 

Not only the teachers and students but other sectors of an educational institution like finance and administration can utilize them properly. 

This will eventually lead to bringing effectiveness, completeness and overall productivity in the overall education sector. Moreover, along with great learning, they will also get creative by predicting all the future aspects. 

Hence there are hundreds of way big data can transform the education sector, but we along with our research team has read and selected the 5 best ways. We made sure to include the most important ones so it turns out to be helpful for our readers. 

Wrapping Up: 

This is the end of our article ‘5 Amazing Ways Big Data is Transforming the Education Sector‘ We hope this article helped you learn about the importance and the way big data can bring positive impact in the education sector if used properly. 

Moreover, if you have any more points that are valuable, feel free to share it with us in the comments section below. 

Big data can actually be a precious gift in the education sector in the upcoming days if used properly. So, make sure to use the big data properly and shine out!

Categories
Business

The best guide to outbound lead generation for 2023

Your outbound lead generation is manually targeting, finding, and acquiring leads or customers. Quite simply stated, does going to a customer your service or products, regardless of if the customer shows an interested party or otherwise? 

The methods used to create outgoing referrals include making cold calls, bulk emails, sending out direct mail, and using and showing commercials. 

Outbound and inbound lead generation

Below, we’ll look at the three main differences between outbound and inbound lead generation. 

№1. Interaction control

The key distinction is in who controls where and when all actions, i.e., sharing and consuming information or content, occur.

Inbound flow strategies enable prospective clients to select the way they engage and interact with your channel by choosing which medium of information they prefer to engage with and the right time for them. For instance, SEO, Social media marketing, etc. 

Lead generation refers to the strategy that lets you, a business, choose when prospective clients receive phone calls, emails, and see ads.

№ 2. The value of marketing assets

Exit drives have a much quicker life span than incoming drives. For instance, in Outbound Lead Generating, ageless Content can produce Leads long-term after they’ve already occurred, thereby giving you a significant long-term ROI for your marketing endeavors.

Outbound leads generated, on the one hand, are short-lived due to high-risk content and high cost. Most of the resources created are not utilized once the company’s launch of the marketing campaign is complete.

№3. Campaign Cost Profile

Lead inbound campaigns cover a wider time frame of time and lower costs. The traffic is earned, not purchased, so there’s no requirement to purchase a return on investment method.

Standard Outbound cost profile cost is high and has short timelines. High costs are due to needing management of rejection risk as well as the relatively greater expense of delivery vehicles used such as soft callers, ads, etc. Lead costs tend to remain the same but can occasionally go up. If the creatives are not up-to-date, then the content will become dull for your intended audiences. You want an SEO firm that will stand by you, will work hard, helps you develop your business, and delivers outstanding quality results.

Outbound lead generation strategies worth trying in 2023

Below, we’ve compiled five basic strategies for attracting potential customers that everyone should try.

№1. Cold emails

A Cold letter is a message you give to a prospective client who doesn’t yet have heard of or know a great deal from your company. A Cold Case Letter builds an opening to begin to build a relationship for years to come. 

An effective cold email contains the following: 

№ 2. Social Media

Using networking social networking sites to market a product or a service to prospective clients can be a great strategy. Prospective clients would be more probable of seeing a message on social networks rather find it easy to contact and communicate efficiently than open an e-mail.

№3. Syndicated content

A portion of this content that is reposted on sites apart from the original site is called syndicated Content. The aim is simply to gain new clients and increase content exposure. 

№ 4. Events

Choose from a variety of events that inform potential buyers about your product:

  • Online courses;
  • Webinars;
  • Live broadcasts; 
  • Seminars;
  • Exhibitions;
  • VIP Impressions;
  • Conferences;
  • Product Launch Parties;
  • Festivals;
  • Networking Session.

№ 5. Paid advertising

Meaning you’re purchasing ad space, commonly known as Pay-per-click ads, where a publisher is paid when the ad is pushed. Advantages included front Page Impressions, a targeting focus, big branding features, constant and instant targeted driving, and measurable traffic, and easy-to-measure analytics.

When you find that leads acquisition drives are consuming you too long, you can use managed search and retrieval (SEO) Services from a reliable SEO agency. That way, you will have more time to get to the bottom line of your core activities at the same time as having your SEO affiliate generate qualifying leads and leads for you.

Categories
Business

What To Learn To Become A Professional Analytic

Professional analytics collect, clean, and analyze data to aid business choices. To work as an analyst, you need to analyze data effectively and draw conclusions from massive amounts of information. Opportunities abound in this field. The reason for this is the massive investment in big data by businesses of all sizes and sectors. If you’re interested in becoming a data analyst and learning more about the job and the industry, keep reading.

 

Required Soft Skills

People who work in this sector need to have a strong intrinsic motivation to study new things and figure out how they work. Analysts must remain abreast of industry developments even after moving up the ranks. Current and future analysts make use of analytical essay ideas, gaining inspiration and new reasons for their logical conclusions. Disclosing analytical essay topics also helps train systematic thinking. Messy information is useless to everyone. Analytics experts who want to extract value from data must have the skills to translate and display data clearly and straightforwardly.

 

An excellent expert in business analytics may be defined as capable of effectively conveying ideas and information. To ensure that all parties comprehend insights and can put suggestions into effect, it is essential to deliver results in a clear and straightforward way. Speaking clearly and effectively in front of an audience is a prerequisite for anybody working in analysis.

 

Analytics experts address issues and advance businesses by using a variety of methods. So being a problem solver by nature is also one of the requirements for a data analyst. Professionals in the field of business analytics must constantly exercise critical thinking. They’re supposed to sift through all the information and emphasize the bits that will assist in making choices. Reading books on the topic is a must.

 

Let’s move from soft skills to hard ones. What makes an excellent professional on a knowledge level? Read on to find out.

Gain A Foundation In Data Analytics

Learning SQL, Python, R, Spark, and Hadoop will help you crunch numbers. Tableau, Matplotlib, and ggplot2 will teach you how to create stunning visuals that bring data to life. These are the initial steps toward becoming a professional. 

 

How to become a data analyst? Specialized programs may be an exceptional method to pick up these foundational skills. They provide a solid grounding on all these platforms. This experience allows a student to get some hands-on practice with the following:

  • data administration
  • formulation of statistical tests
  • syntax of programming languages
  • purifying data
  • graphical representation of info.

Exercise Your Data Analytics Skills With Project Work

Learning to use fundamental resources is essential to pursue a career in the field. To be successful, data analysts need to be abreast of the most recent developments in data analysis technology. Writing a research paper, browsing through thematic websites, and reading new professional literature are habits of a pro. Develop sample projects that include all aspects of data analysis. Your work should include things from the initial company and market exploration to defining the specifics of the data to be gathered and cleaned. 

 

Finally, visualize the findings you’ve uncovered. Try putting them into a dashboard that will let others engage with your information. Take on various practice projects to hone your skills and showcase your knowledge of data mining across several formats.

 

How to get a data analyst job? One of the most crucial tasks is figuring out how you will show your expertise. Building a professional portfolio is important. A good place to start is by posting the code you’ve created to demonstrate your skills. One method to present skills and impress prospective employers is to complete a perfect data project. Select a topic that piques your interest, formulate a related query, and see if you can find an answer using data.

Reasons To Become A Professional Analytic

It’s work that fulfills you. This job is rewarding since you solve challenges and see your ideas come to fruition using a computer. With great demand comes hefty compensation. Companies have a hard time filling open positions for data analysts because of the high demand for their services. An average data analyst salary is around $52000. Also, career options may be adjusted to fit your needs. You may work from home, for a startup, an agency, or a huge corporation. There are a number of flexible settings.

Conclusion

It may be challenging for professionals to determine where to best direct their development efforts. Despite the dynamic nature of the sector, a thorough grounding in a few areas is essential for any professional’s success. We hope that our article and presented examples helped you discover crucial steps to a successful career as a data analyst.