What common services do big data analytics and business intelligence companies offer?
Big data companies offer the following solutions for businesses looking to expand their services:
Data warehousing: A data warehouse is a centralized repository of structured data that is stored after analysis for businesses’ use. Data warehousing or data management is the process of managing the centralized repository to provide you with quickly accessible and shareable data files.
Data migration: Data migration is the process of transferring a data set from one database to another for further processing, storing, and sharing. The migration facility helps save time and the effort of manually entering data from one database to another.
Data visualization: Data visualization is the graphical representation of data and information in the form of charts and graphs, among other visual elements. The analysis of raw unstructured data is represented by bar graphs and pie charts for better understanding.
Data modeling: Data modeling is the process of organizing unstructured data to understand its flow and relationships between different data points. Having an organized database provides clarity while assessing and interpreting data for business decisions.
Data discovery: Data discovery, also known as data mining, is the process of discovering patterns in large data sets. The data is discovered using technology algorithms such as AI and ML.
Data cleaning: Data cleaning is the process of detecting, correcting, or removing corrupt or inaccurate data from a data set or an entire database. Data cleaning tools are used to search the data sets for missing values and duplicate values to avoid errors and gaps in the decision-making process.
Business intelligence companies offer a variety of services for businesses looking to gain data insights. Here’s a list of the services most agencies provide:
Data preparation: Business intelligence agencies offer data preparation services to help capture, clean, and combine raw data into curated datasets for analysis. This process eliminates errors and inconsistencies such as repetitive or missing data points from the captured data. It prepares the raw data for analysis and removes inaccuracies to deliver better insights.
Data storytelling: Business intelligence companies offer data storytelling services to present business insights and trends using narrative and data visualization techniques, such as pictures, graphics, and BI dashboards and storyboards. This process helps deliver compelling yet simple data analysis reports for faster decision-making.
Data modeling: Business intelligence agencies provide data modeling services to analyze data and identify the relationships between different data points. Having interrelated data points together helps businesses ensure a consistent flow of information for informed decision-making.
Advanced data analytics: For advanced data analytics, agencies use quantitative methods to produce insights that are unlikely to be discovered through traditional approaches to business intelligence. Predictive, prescriptive, and artificial intelligence techniques are used to interpret events, automate decisions, take data-backed actions, and more.
Business intelligence vs data analytics: What's the difference?
The terms "business intelligence" and "data analytics" are often used interchangeably, even though there is a considerable difference between the two. Another common misconception is that business intelligence strictly focuses on historical data, and data analytics attempts to predict future trends. In reality, there is some overlap between both of these approaches, while their differences lie in how data is collected and interpreted.
Business intelligence (BI) refers to software and other technologies that collect and integrate data to aid decision-making. BI applications help managers and other business leaders visualize data to make trends easier to understand. Meanwhile, data analytics applies complex algorithms to big data sets to help find relationships between data that aren't readily apparent. Whereas BI is more of a day-to-day tool that allows managers and supervisors to make operational decisions, data analytics presents technical patterns and correlations that require expert interpretation from the raw data.
What are the types of big data analytics companies?
A few different types of big data services companies include:
Strategy and consulting services companies that put a strong emphasis on creating data and analytics vision, strategy, or operational models within the context of the larger company goals and objectives. This is similar to platform partner companies that provide integration or optimization advisory services associated with specific platforms or technologies.
Data and analytics governance services companies that specialize in the creation and implementation of data and analytics structures, processes, techniques, and technologies into current business processes.
Analytics and business intelligence services companies that provide analytics and business intelligence platform integration for businesses to build reports, analyses, visualizations, and advanced analytics models.
Data science services companies that make use of AI, ML, and other quantitative methods to analyze numerical data using statistical models.
What are the benefits of hiring a big data analytics company?
Partnering with third-party data analytics companies can benefit you in the following ways.
Objective data analysis: Systematic errors in human thinking, or cognitive biases, are the key driver for biased data analysis. Such biases occur when in-house data analysts process and interpret information based on the perspective of their surrounding people. While analyzing data, third-party data analytics service providers are devoid of any biases or prejudices which may impact the decision-making process. They make use of technology tools that eliminate any errors or biased approaches while processing data. This leads to an unbiased and objectively correct data interpretation.
Domain expertise and experience: Big data companies have the expertise to understand common challenges that businesses face when analyzing data. Having vast industry exposure helps maintain accuracy and relevancy in the delivered business insights. Besides, partnering with a big data company that has previously worked with a similar industry domain and has the exposure of handling the desired technical ecosystem (tools/platform) is a value-add.
Cost-effectiveness: Data analytics resources such as technology tools and skilled professionals are expensive and come with a limited resource pool. In addition, these resources are difficult to be fully utilized in-house for consistent results. All these challenges direct companies to partner with data analytics companies when the need arises.
Who should hire a big data analytics company?
Big data is important because it is the key driver for businesses to understand their customer/client problems and provide solutions. The solution could be anything—adding new products, enhancing the features of the existing products, custom software development, or mobile app development.
If your business heavily relies on data for revenue generation, you should hire a big data analytics company. It will help you meet your desired business goals and objectives with access to accurate information. Besides, other businesses can partner with big data companies to overcome challenges and unlock opportunities through data.
Who should hire a business intelligence services company?
Hiring a business intelligence services company is the right choice for:
Companies that can’t leverage their business data for decision-making: Capturing and analyzing business data, such as big data, requires specialized skills. Professionals such as data scientists have the expertise required to uncover actionable insights from raw data. Business intelligence companies have a team of data science and analytics experts who analyze your organization’s raw data to identify business challenges and develop the right solutions. These companies also assist in deploying the developed solutions into your existing workflows to ensure your business achieves its desired outcome.
Companies that lack in-house business intelligence tools: Not all companies have in-house tools to capture, consolidate, and analyze data to identify key business trends and opportunities. Inadequate or insufficient data analysis can lead to inaccurate decision-making. Such companies can partner with business intelligence services agencies to get assistance with smart and efficient decision-making.
How much does it cost to hire a big data services company?
The cost to hire a big data services company is available on quote. The companies have varied pricing structures depending on the types of big data services offered. Some of the pricing models data analytics companies typically follow are:
Hourly pricing model: In this model, data analytics companies with a team of analysts charge a specific amount for every hour of work they do. The price is based on the number of people involved and the hours they spent working on a project. The cost of their services also varies based on the types of professionals involved, such as industry specialists or general analysts.
Project-based pricing model: In this pricing model, data analytics companies charge at once for all the desired solutions. In some cases, the service provider asks for the entire project cost beforehand, while others prefer a small percentage of the total cost (15% to 20%) and the rest at the time of delivery.
How much does it cost to hire a business intelligence services company?
Business intelligence agencies have varied pricing structures, so it’s difficult to define the exact cost of hiring their services. Listed below are the common pricing models you can avail:
Hourly pricing model: In this model, business intelligence agencies charge a specific amount per hour. Most agencies decide the amount based on the type of data preparation, modeling, or analysis services you need. The cost of services could also vary if you want to hire more seasoned data science or analysis experts.
Project based pricing model: Many business intelligence companies follow a project-based pricing model—also known as a flat-fee pricing model—wherein they discuss and estimate the entire project cost with the client beforehand. The cost could go up if your business wants advanced data analytics capabilities. This model is suitable for long-term projects that need multiple iterations or upgrades. Agencies that follow a project-based model usually ask for an upfront fee (15% to 20% of the entire project cost) at the start of the project.
Monthly pricing model: In this pricing model, business intelligence companies offer a monthly subscription plan. It’s a tiered pricing model wherein the subscription price increases with each newly added service. Users have the flexibility to pay upfront for an entire year or set a recurring transaction for each month.
How to select a big data analytics company
Here are some considerations to keep in mind when selecting a big data analytics company for your business:
Check industry knowledge: You need to check if your selected data analytics company knows your industry and type of business. The company should specialize in your industry or have had work experience with similar businesses.
Analyze offered services: Select a data analytics company with features that align with your business requirements. For instance, you may require a specific type of analysis, such as predictive or descriptive analytics.
Assess data security: Your business’s data and information play a critical role in its growth. Therefore, you need to ensure it is secure when shared with an external source. Check the type of security and accessibility controls, including security infrastructure, cybersecurity measures, and compliance considerations offered by your shortlisted data analytics company to see if they can keep your data safe from unauthorized access.
Check the use-case requirements: Make sure that you have the required resources to work hand-in-hand with the big data company you partner with. They may be experts in all things analytics and big data management, but your input into the specifics of your business and use case requirements are critical success factors. In addition, check if the company has worked through any pre-onboarding/implementation and post-offboarding/migration tasks beforehand to mitigate risks and get the most out of your investment.
How to select a business intelligence services company
These are a few considerations to keep in mind when hiring a business intelligence services agency:
Consider your data analysis requirements. Your business may need insights into the overall processes or a specific function. So, first, prepare a list of your data analysis requirements. Are you trying to capture unique website visitors? Do you wish to know how customers feel about your offerings? Do you want to identify the reason your customers are leaving? After defining your data analysis needs, shortlist a service provider that has the business intelligence tools and techniques to satisfactorily address your data requirements.
Assess the provider’s portfolio. To understand whether a BI service provider can help your business achieve its desired goals, assess their previous projects, industry experience, and knowledge of trends. Research the type of organizations the service provider has previously partnered with and the variety of business intelligence services they offer. This will help you assess if the provider has the expertise to address challenges specific to your business type or industry.